Dissertations / Theses on the topic 'ARCS Motivational Design Model'

Blended and online courses can require more student self-regulation than traditional in-person courses. Instructors and course designers can support student motivation and self-regulation in a variety of ways, such as by including motivational strategies in the course materials. The purpose of this study was to explore the relationship between the following three factors: the motivational strategies employed in the online course materials of a blended German language course, student engagement in the course, and student usage of the course materials. Selected course activities were analyzed using a checklist based on Keller's ARCS (Attention, Relevance, Confidence, Satisfaction) model for motivational design to identify the motivational strategies that were present. At the end of each unit, students completed surveys about their level of engagement with the online portions of the blended course and their perceptions of the online activities. At the end of the semester, data about student usage of the online activities was collected from the Canvas Learning Management System. The results of this study show that a wide range of motivational strategies are used in the online materials of this course and that students were highly engaged in this course. Students found the grammar and vocabulary activities to be the most motivating and the most useful for their language learning. The number of Attention strategies in an activity was strongly correlated with how often students used the activity, and the number of Attention strategies also predicted how often students would use the activities, likely because Attention strategies increase ease of use of the materials and encourage student curiosity. The number of Satisfaction strategies in an activity predicted how motivating students would find the activity, likely because Satisfaction strategies allowed students to use their new skills in realistic contexts and experience intrinsic and extrinsic rewards. There was a strong correlation between how motivating students found an activity and how useful they found the activity for their language learning. Including more motivational strategies, particularly Attention and Satisfaction strategies, can enhance the student experience and increase student motivation; however, students are most likely to be motivated by activities that they find useful for their language learning.

Våren 2020 genomförde pedagoger från 2047 Science Center (2047) undervisning i teknik i grundskolor i Falu Kommun. Ämnet för insatsen var automatisering, programmering och dess påverkan på individ och samhälle och riktades till elever i årskurs 7. Utöver de mål som följer av skolans styrdokument fanns en strävan att eleverna skulle uppleva undervisningen som relevant. Syftet med denna studie var att undersöka hur 2047 Science Center arbetat med målet att göra sin undervisning relevant för eleverna, och vilket resultat det gav. Studien undersöker elevernas perspektiv på relevans, att undervisningen upplevs som viktig för dem i förhållande till deras intressen eller mål. Viktig blir den, enligt Self-determination Theory, om den bidrar till vårt behov av att uppleva kompetens, autonomi och tillhörighet. Styrkan i vår motivation beror sedan på hur högt vi värderar detta viktiga, och vår förväntan att nå det, enligt Expectancy-Value Theory. För att undersöka undervisningens design för relevans analyserades undervisningen utifrån ARCS-modellen för utformning av undervisning för motivation till lärande (Keller, 2010). Elevernas respons på undervisningen undersöktes sedan med en enkät i sex klasser på tre skolor i kommunen. Resultatet visade att samtliga av Kellers tre koncept för relevans i undervisning; målorientering, matcha motiv och förtrogenhet, beaktas vid utformningen av kursen. De användes också vid ett flertal tillfällen och på olika sätt. Elevernas respons på kursen visade sig vara övervägande positiv. På de fyra påståendena om upplevelsen av undervisningens relevans svarade mellan 55 och 75% av eleverna att det stämde ganska bra eller bra. Innehållets generella nytta, rankades högre än det egna intresset. Denna studie har visat att man kan utforma undervisning så att den ökar elevernas upplevelse av relevans. Tidigare forskning, och studiens resultat, antyder dock att stoffets relevans är en nödvändig, men inte tillräcklig, förutsättning för elevernas upplevelse av relevans. Läraren måste först få elevernas uppmärksamhet, och klassens sociala norm behöver tillåta deras engagemang och lärande.

Teknik

The purpose of this study was to investigate the perceptions of learners in the blended course relative to the use of Seven Principles for Good Practice in Undergraduate Education. Additionally through the motivational requirements specified by Keller&rsquo
s ARCS motivational design model, students&rsquo
motivations were analyzed. Thus the study was designed to determine student motivation in a blended environment in relation to Keller&rsquo
s ARCS motivational design model. For these research aims, a traditional course was redesigned with the support of online applications by taking Good Practice Principles as the framework. A triangulation mixed method approach was utilized as the primary design of the study by employing both qualitative and quantitative methods in a single study. The study participants included 47 preservice teachers in an undergraduate teacher education program of Computer Education and Instructional Technology Department in the Middle East Technical University who took the course (School Experience I) in blended design mode in 2005-2006 spring semester. Qualitative and quantitative data were collected through three different surveys, student interviews, and forum transcripts. The data were analyzed concurrently according to both qualitative and quantitative data analysis techniques. The analyses of qualitative and quantitative data showed that students&rsquo
perceptions in the blended course and perceptions in relation to each good teaching principles were mostly positive. Results reveal that students perceive six of the principles including student faculty contact, cooperation, time on task, diversity and ways of learning, feedback, and active learning helpful to their learning. Additionally, the students think that the other one principle which is expectations needs to be improved. In addition, high motivation scores were gathered in the blended course. Results show that attention, relevance, confidence, and satisfaction subscores revealed significantly higher levels of motivation among students.

Doctor of Philosophy
Curriculum and Instruction
Rosemary Talab
The purpose of this study was to examine student motivation in a blended learning digital literacy course and its relation to student characteristics. The study consisted of 136 student participants enrolled in a blended learning digital literacy course at a Midwestern university. The Keller ARCS Motivation Model was the theoretical framework. The Course Interest Survey was used in the study, which was designed to measure motivation using Keller ARCS categories. Data was collected through the Course Interest Survey to voluntary student participants and through data obtained from the research setting. The study examined the following research questions: Research Question 1: Do statistically significant relationships exist between non-performance student characteristics and the Keller ARCS Course Interest Survey student motivation scores in a blended digital literacy course? Research Question 2: Do statistically significant relationships exist between pre-course performance student characteristics and the Keller ARCS Course Interest Survey scores in a blended digital literacy course? Research Question 3: Do statistically significant relationships exist between post-course performance student characteristics and the Keller ARCS Course Interest Survey student motivation scores in a blended digital literacy course? To examine these relationships, the study utilized MANOVAs to analyze the student characteristics on the four categories of the Keller ARCS Motivation Model. One significant relationship was found for Confidence within Academic Rank (p < .05), between Seniors and Freshmen. Seniors reported a .4799 higher Confidence score, on average, than Freshmen. Other characteristics did not have significant relationships. The mean change in pretest and posttest scores in digital literacy on the ALTSA assessment was 6.64. Recommendations for the research setting included the use of student focus groups to better understand and increase Freshmen confidence and the Freshmen experience, a review of course design and delivery methods, an exploration of variations of blended learning models, an examination of current test-out procedures, and adjustment of the scale used in this study to provide a wider range of motivation responses. Recommendations for future studies included a qualitative study of student performance characteristics, a mixed methods study of different learning models for course delivery, and an exploratory study aimed at expanding student characteristics.

Supporting retention, student success, and online enrollments are some of the most significant and challenging topics in higher education today. Students who fail to succeed early in their studies are less likely to be retained, and students in the online environment are more likely to fail than their campus counterparts. Motivational techniques have been shown to support course retention and success, but studies of online motivational course support methods are limited. Some evidence exists that motivational messages can affect student performance in online courses, but the message format that is most effective has yet to be definitively established. A survey research design was employed and quantitative and qualitative data were collected to determine how motivational messages and message type affect student performance and retention in an introductory online community college course. The population consisted of students in three sections of an introductory online IT course. The data included student course grades, final course scores, responses to three surveys, and the researcher's reflexive journal of motivational message design decisions made throughout the course. Due to low course participation levels and low survey return rates, only the descriptive data were reported. Additional exploration of the literature to explain low participation was sought. Potential causes for low survey return rates included low course participation, survey length, the number of survey contacts, inaccurate estimates of survey completion time, and the number of surveys deployed. To explain the low course participation, best practices with regard to online course design were identified in the literature and compared to the design of the course used in this study. Qualitative survey results and a reflexive journal of the researcher's design decisions are also presented. The results suggest that students liked the motivational messages. The reaction was stronger for the personalized messages than for the general, but this was not a conclusive finding. To the contrary the findings suggest that motivational messages (regardless of type) are not by themselves effective at engaging and retaining students and should not be used as a stand-alone motivational technique.

Abstract Chronic conditions are the leading cause of death in the world. Major improvements in acute care and diagnostics have created a tendency towards the chronification of formerly terminal conditions, requiring people with these conditions to learn how to self-manage. Mobile technologies hold promise as self-management tools due to their ubiquity and cost-effectiveness. The delivery of health-related services through the use of mobile technologies (mHealth) has grown exponentially in recent years. However, only a fraction of these solutions takes into consideration the views of relevant stakeholders like healthcare professionals or even patients. The use of behavioral change models (BCM) has proven important in developing successful health solutions, yet engaging patients remains a challenge. There is a trend in mHealth solutions called gamification that attempts to use game elements to drive user behavior and increase engagement. As it stands, designers of mHealth solutions for behavioral change in chronic conditions have no clear way of deciding what factors are relevant to consider. This doctoral thesis is framed in Consumer Health Informatics within the field of Medical Informatics and Information Systems. The focus of this work was to discover factors for the design of mHealth solutions for chronic patients; to do so, negotiations between medical knowledge, BCM and gamification were explored through an embedded case study research methodology. The data obtained was thematically analyzed to create the Model for Motivational Mobile-health Design for Chronic conditions (3MD). The 3MD model guides the design of condition-oriented gamified behavioral change mHealth solutions. The main components are: 1) Condition specific, which describe factors that need to be adjusted and adapted for each particular chronic condition; 2) Motivation related, which are factors that address how to influence behaviors in an engaging manner; and 3) Technology based, which are factors that are directly connected to the technical capabilities of mobile technologies. 3MD also provides a series of high level illustrative design questions for designers to use and consider during the design process. The work on this thesis addresses a recognized gap in research and practice, and proposes a unique model that could be of use in the generation of new solutions to help chronic patients
Tiivistelmä Krooniset sairaudet ovat maailman yleisin kuolinsyy. Akuutissa hoidossa ja diagnostiikassa on tapahtunut merkittäviä parannuksia, ja aikaisemmin kuolemaan johtaneista sairauksista on tullut kroonisia ja ihmisten on opittava hallitsemaan niitä itse. Mobiiliteknologiat tarjoavat mahdollisuuksia sairauksien itsehallintaan, koska teknologiaa on yleisesti saatavilla ja se on kustannustehokasta. Terveyspalvelujen tarjoaminen mobiiliteknologian avulla on lisääntynyt huomattavasti viime vuosina. Kuitenkin vain murto-osa näistä ratkaisuista ottaa huomioon sidosryhmien, kuten terveydenhuollon ammattilaisten ja jopa potilaiden, näkemykset. Käyttäytymismuutosmallit ovat osoittautuneet tärkeiksi kehitettäessä onnistuneita terveysratkaisuja, mutta potilaiden osallistaminen kehittämiseen on yhä vaikeaa. Pelillistäminen on mobiilien terveysratkaisujen suunnittelutrendi, ja pelielementeillä pyritään vaikuttamaan ihmisten käyttäytymiseen ja sitoutumiseen. Mobiilien terveyssovellusten suunnittelijoilla ei ole selkeää näkemystä siitä, mitkä sovellustekijät vaikuttavat merkittävimmin kroonisissa sairauksissa sairastavien potilaiden käyttäytymisen muutokseen. Tämä väitöskirja tarkastelee kuluttajille suunnattua terveysteknologiaa, joka hyödyntää lääketieteellistä informatiikkaa ja tietojärjestelmätieteitä. Työn tavoitteena oli selvittää kroonisia sairauksia sairastaville potilaille tarkoitettujen mobiilien terveyssovellusten suunnitteluun liittyviä tekijöitä. Tämän vuoksi lääketieteen tietämyksen, käyttäytymismuutoksien mallien ja pelillistämisen yhdistämistä tutkittiin sulautetun tapaustutkimuksen avulla. Saatuja tietoja temaattisesti analysoimalla luotiin kroonisia sairauksia varten motivoivan mobiilin terveyssovelluksen suunnittelumalli (3MD = Model for Motivational Mobile-health Design). 3MD-malli ohjaa sairauksien hallintaan tarkoitettujen pelillistettyjen ja käyttäytymismuutoksiin tähtäävien mobiilien terveyssovellusten suunnittelua. Mallin pääkomponentit ovat: 1) Sairautta kuvaavat tekijät, jotka kuvaavat tekijöitä, jotka on mukautettava ja sovitettava kullekin krooniselle sairaudelle. 2) Motivaatioon liittyvät tekijät, jotka vaikuttavat innostavasti käyttäytymiseen. 3) Teknologiaan perustuvat tekijät, jotka liittyvät suoraan mobiiliteknologian teknisiin ominaisuuksiin. 3MD tarjoaa myös havainnollisia suunnittelukysymyksiä, joita suunnittelijat voivat käyttää ja pohtia suunnitteluprosessin aikana. Tämä väitöskirja käsittelee yleisesti tunnistettua puutetta tutkimuksessa ja suunnittelukäytännössä ja esittelee ainutlaatuisen mallin, josta voi olla hyötyä uusien ratkaisujen luomisessa ja kroonisia sairauksia sairastavien potilaiden auttamisessa

The primary purpose of this study was to determine whether external conditions, in the form of an e-learning tool, impact the learning motivation of adult learners in a distance education environment. This study also tested the use of Voice-over-PowerPoint™ technology as a suitable medium to deliver motivational instruction as supplementary content to the course curriculum. This empirical study was conducted over a period of approximately two months on a sample of 57 adult learners who were enrolled for a distance education course for non-degree purposes at a tertiary education institution. Quantitative research methods were applied and data was collected using two motivation measuring surveys: (1) The Course Interest Survey, and (2) The Instructional Materials Motivation Survey, which were both developed by Keller. Motivational strategies were designed for the chosen educational technology, Voice-over-PowerPoint™ (VoP) videos, using Keller's Attention, Relevance, Confidence and Satisfaction (ARCS) model of motivation. These strategies were then delivered via the learner management system for learners to use at their convenience. This research suggests that overall, learner motivation can be affected by external conditions (VoP videos), and further supports the ARCS model. Furthermore, the use of VoP videos as a viable medium for delivering motivational strategies in a distance learning environment was validated.
Mini Dissertation (MCom)--University of Pretoria, 2016.
Taxation
MCom
Unrestricted

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, June 2005.
Includes bibliographical references (leaves 33-34).
Motivation is a subject of great interest to managers seeking to improve overall team performance. Furthermore, motivation has been my greatest challenge as team manager of the MIT Motorsports Formula SAE team. This group is composed of volunteer students dedicating their time for an extra-curricular activity. This thesis serves to develop a motivational model unique to MIT Motorsports with the goal of increasing overall team performance. MIT Motorsports team dynamics are described through performance observations and feedback from a survey given to team members. This analysis is combined with a discussion of traditional and contemporary theories of motivation to yield a new improved model of motivation. Conclusions of this thesis are particularly useful for future MIT Motorsports team managers. While this model is specific to MIT Motorsports, the overall approach to the universal problem can enlighten any manager seeking to receive gains from the motivation to performance relationship.
by Joseph M. Audette.
S.B.

National and International statistics (WHO 2001) demonsrates that it remains easier to motivate women to initiate breastfeedmg than sustain It. evidence highlights two motivational factors, women lack confidence and professional support (Avery et al. 1998, Dodgson et al. 2003, Chezem et al. 2003). It was theorized that if midwives' instruction was confidence-building, woman's persistence would increase. The research aim was to develop and test a motivational intervention using the ARCS Model of Motivational instructional Design (Keller 1987). Method: Four phases of the ARCS model rdlected an Action Research design. Phase one analysed current instruction by applying Sansone and Harackiewicz (1991) goal conceptualization as a structure for a participant observation study (n=130 women and 20 educators). A second observation study, re-applied the structure to breastfeeding websites n=30). Outcomes revealed instructional confidence and relevance deficits. Phase two assessed the motivational effects of the observed instruction. A theoretical measurement tool was developed toranalyze audience motivation. A convenience sample (n=202) of post-natal women who were breastfeeding consented to complete the questionnaire. Outcomes of Exploratory Factor Analysis confirmed the validity of confidence and relevance deficits. Phase three defined the motivational objectives and selected strategies from the ARCS model for embedment into current instruction. The resulting intervention 'Designer Breastfeeding' included a motivational version ofantenatal instruction, breastfeeding web-site and postnatal midwife support. A pilot study (n=20) resulted in the discontinuation ofthe web-site. Phase four experimentally tested 'Designer Breastfeeding' with Baby Friendly Initiative instruction. First-time mothers (n=182) were recruited to a RCT. Women's motivation was measured using the diagnostic measurement tool. The questionnaire was completed pior to discharge from hospital. Telephone follow-up confirmed breastfeeding maintenance at three weeks. 'Designer Breastfeeding' significantly increased maternal confidence (p<.001), perceived midwife support (P<.001) and persistence to breastfeed (P<.001).

Maternal overweight and obesity is associated with adverse pregnancy outcomes. Both women and healthcare professionals have expressed a desire for resources to adequately support pregnant women in successful weight management. The primary aim of this research was to identify any motivational deficits for healthy diet and physical activity behaviours in first-time mothers receiving routine antenatal education and in response develop an intervention that solved these deficits, therefore improving optimal weight gain during pregnancy. Application of the ARCS Model of Motivational Instructional Design (Keller, 1987) was undertaken using a mixed method approach with six interrelated phases: Phase one: Goal setting interventions for improving weight management during pregnancy were identified through a systematic literature review. Phase two: A motivational analysis of current antenatal instruction through non-participant observation. Phase three: Maternal motivation to eat a healthy diet and exercise was explored through one-to-one telephone interviews (n=9) and a theoretical measurement tool was developed and validated in a convenience sample (n= 196) of first-time mothers Phase four: Evidence generated in phases 1-3 was collated to create an overall audience motivational profile where lack of confidence-building instruction was identified as the key motivational problem. Phase five: Motivational objectives were established and appropriate ARCS model strategies selected to solve motivational deficits. Phase six: A new resource: "Yummy Tummies" was created and evaluated positively by maternity staff and women (n=11).

There is a lack of empirical research on the motivational regulation and reactions of higher education students enrolled in blended courses. Studies that target this focus with nontraditional adult learners enrolled in the community college are even more difficult to locate. In this mixed-methods exploratory case study, I explored in what ways nontraditional adult learners' motivational regulation and their motivational reactions to course design relate to their perceived learning experience in a blended technology course with a flipped design. Specifically, I investigated how nontraditional community college students described their goals for participating in a blended course prior to the start of the class, in what ways they utilized motivational regulation strategies within the course, how they described their motivational reactions to a blended course developed with a flipped design, and how they perceived their goal accomplishments at the end of the course. The following A Priori questions guided my research: 1. In what ways do five nontraditional community college students describe their goals for participating in a blended technology course with a flipped design prior to the start of the class? 2. How do these students describe their motivational regulation experiences in the blended technology course on their responses to the Motivational Regulation Strategies Questionnaire? 3. How do these students perceive the motivational aspects of the course design as measured by the Course Interest Survey? 4. In what ways do these students perceive they achieved their described goals at the end of the course? I collected quantitative and qualitative data in the Fall semester of 2017 from five purposefully selected nontraditional adult community college learners who voluntarily engaged in the inquiry. I used several data collection instruments throughout the study. I collected quantitative data via three questionnaires: (1) a Demographics, Goals, and Interest Survey (2) the Motivational Regulation Strategies questionnaire, and (3) the Course Interest Survey. I gathered qualitative data through (1) participant electronic journals, (2) semi-structured interviews and (3) a researcher's reflective journal. There are both practical and theoretical implications to this study. The results of this research suggest guidelines on how to design an effective blended course for nontraditional students enrolled in the community college arena. The information gleaned might be used to further develop and redesign future blended courses for nontraditional community college students who seek alternative modes of content delivery for the purposes of continued learning and convenience of integration into their busy lifestyles. The findings from this study contribute to at least two bodies of empirical research literature: (1) motivational regulation strategies employed by nontraditional community college students and the (2) development of blended courses with motivational design to help nontraditional community college adult learners obtain their learning goals.

Many online learning technologies grant students great autonomy and control, which imposes high demands for self-regulated learning (SRL) skills. With the fast development of online learning technologies, helping students acquire SRL skills becomes critical to student learning. Theories of SRL emphasize that making problem selection decisions is a critical SRL skill. Research has shown that appropriate problem selection that fit with students’ knowledge level will lead to effective and efficient learning. However, it has also been found that students are not good at making problem selection decisions, especially young learners. It is critical to help students become skilled in selecting appropriate problems in different learning technologies that offer learner control. I studied this question using, as platform, a technology called Intelligent Tutoring Systems (ITSs), a type of advanced learning technology that has proven to be effective in supporting students’ domain level learning. It has also been used to help students learn SRL skills such as help-seeking and self-assessment. However, it is an open question whether ITS can be designed to support students’ learning of problem selection skills that will have lasting effects on their problem selection decisions and future learning when the tutor support is not in effect. ITSs are good at adaptively selecting problems for students based on algorithms like Cognitive Mastery. It is likely, but unproven, that ITS problem selection algorithms could be used to provide tutoring on students’ problem selection skills through features like explicit instructions and instant feedback. Furthermore, theories of SRL emphasize the important role of motivations in facilitating effective SRL processes, but not much prior work in ITS has integrated designs that could foster the motivations (i.e., motivational design) to stimulate and sustain effective problem selection behaviors. Lastly, although students generally appreciate having learner control, prior research has found mixed results concerning the effects of learner control on students’ domain level learning outcomes and motivation. There is need to investigate how learner control over problem selection can be designed in learning technologies to enhance students’ learning and motivation. My dissertation work consists of two parts. The first part focuses on creating and scaffolding shared student/system control over problem selection in ITSs by redesigning an Open Learner Model (OLM, visualizations of learning analytics that show students’ learning progress) and integrating gamification features to enhance students’ domain level learning and enjoyment. I conducted three classroom experiments with a total of 566 7th and 8th grade students to investigate the effectiveness of these new designs. The results of the experiments show that an OLM can be designed to support students’ self-assessment and problem selection, resulting in greater learning gains in an ITS when shared control over problem selection is enabled. The experiments also showed that a combination of gamification features (rewards plus allowing re-practice of completed problems, a common game design pattern) integrated with shared control was detrimental to student learning. In the second part of my dissertation, I apply motivational design and user-centered design techniques to extend an ITS with shared control over problem selection so that it helps students learn problem selection skills, with a lasting effect on their problem selection decisions and future learning. I designed a set iv of tutor features that aim at fostering a mastery-approach orientation and learning of a specific problem selection rule, the Mastery Rule. (I will refer to these features as the mastery-oriented features.) I conducted a fourth classroom experiment with 200 6th – 8th grade students to investigate the effectiveness of shared control with mastery-oriented features on students’ domain level learning outcomes, problem selection skills and enjoyment. This experiment also measured whether there were lasting effects of the mastery-oriented shared control on students’ problem selection decisions and learning in new tutor units. The results of the experiment show that shared control over problem selection accompanied by the mastery-oriented features leads to significantly better learning outcomes, as compared to full system-controlled problem selection in the ITS. Furthermore, the mastery-oriented shared control has lasting effects on students’ declarative knowledge of problem selection skills. Nevertheless, there was no effect on future problem selection and future learning, possibly because the tutor greatly facilitated problem selection (through its OLM and badges). My dissertation contributes to the literatures on the effects of learner control on students’ domain level learning outcomes in learning technologies. Specifically, I have shown that a form of learner control (i.e., shared control over problem selection, with mastery-oriented features) can lead to superior learning outcomes than system-controlled problem selection, whereas most prior work has found results in favor of system control. I have also demonstrated that Open Learner Models can be designed to enhance student learning when shared control over problem selection is provided. Further, I have identified a specific combination of gamification features integrated with shared control that may be detrimental to student learning. A second line of contributions of my dissertation concerns research on supporting SRL in ITSs. My work demonstrates that supporting SRL processes in ITSs can lead to improved domain level learning outcomes. It also shows that the shared control with mastery-oriented features have lasting effects on improving students’ declarative knowledge of problem selection skills. Regarding using ITSs to help students learn problem selection skill, the user-centered motivational design identifies mastery-approach orientation as important design focus plus tutor features that can support problem selection in a mastery-oriented way. Lastly, the dissertation contributes to human-computer interaction by generating design recommendations for how to design learner control over problem selection in learning technologies that can support students’ domain level learning, motivation and SRL.

Many functions that at one time could only be performed by humans can nowadays be carried out by machines. Automation impacts many areas of life including work, home, communication and mobility. In the driving context, in-vehicle automation is considered to provide solutions for environmental, economic, safety and societal challenges. However, automation changes the driving task and the human-machine interaction. Thus, the expected benefit of in-vehicle automation can be undermined by changes in drivers’ behaviour, i.e. behavioural adaptation. This PhD project focuses on motivational as well as higher cognitive processes underlying behavioural adaptation when interacting with in-vehicle automation. Motivational processes include the development of trust and acceptance, whereas higher cognitive processes comprise the learning process as well as the development of mental models and Situation Awareness (SA). As an example for in-vehicle automation, the advanced driver assistance system Adaptive Cruise Control (ACC) was investigated. ACC automates speed and distance control by maintaining a constant set cruising speed and automatically adjusting vehicle’s velocity in order to provide a specified distance to the preceding vehicle. However, due to sensor limitations, not every situation can be handled by the system and therefore driver intervention is required. Trust, acceptance and an appropriate mental model of the system functionality are considered key variables for adequate use and appropriate SA. To systematically investigate changes in motivational and higher cognitive processes, a driving simulator as well as an on-road study were carried out. Both of the studies were conducted using a repeated-measures design, taking into account the process character, i.e. changes over time. The main focus was on the development of trust, acceptance and the mental model of novice users when interacting with ACC. By now, only few studies have attempted to assess changes in higher level cognitive processes, due to methodological difficulties posed by the dynamic task of driving. Therefore, this PhD project aimed at the elaboration and validation of innovative methods for assessing higher cognitive processes, with an emphasis on SA and mental models. In addition, a new approach for analyzing big and heterogeneous data in social science was developed, based on the use of relational databases. The driving simulator study investigated the effect of divergent initial mental models of ACC (i.e., varying according to correctness) on trust, acceptance and mental model evolvement. A longitudinal study design was applied, using a two-way (3×3) repeated measures mixed design with a matched sample of 51 subjects. Three experimental groups received (1) a correct ACC description, (2) an incomplete and idealised account omitting potential problems, and (3) an incorrect description including non-occurring problems. All subjects drove a 56-km track of highway with an identical ACC system, three times, and within a period of 6 weeks. Results showed that after using the system, participants’ mental model of ACC converged towards the profile of the correct group. Non-experienced problems tended to disappear from the mental model network when they were not activated by experience. Trust and acceptance grew steadily for the correct condition. The same trend was observed for the group with non-occurring problems, starting from a lower initial level. Omitted problems in the incomplete group led to a constant decrease in trust and acceptance without recovery. This indicates that automation failures do not negatively affect trust and acceptance if they are known beforehand. During each drive, participants continuously completed a visual secondary task, the Surrogate Reference Task (SURT). The frequency of task completion was used as objective online-measure for SA, based on the principle that situationally aware driver would reduce the engagement in the secondary task if they expect potentially critical situations. Results showed that correctly informed drivers were aware of potential system limitations and reduced their engagement in the secondary task when such situations arose. Participants with no information about limitations became only aware after first encounter and reduced secondary task engagement in corresponding situations during subsequent trials. However, trust and acceptance in the system declined over time due to the unexpected failures. Non occurring limitations tended to drop from the mental model and resulted in reduced SA already in the second trial. The on-road study investigated the learning process, as well as the development of trust, acceptance and the mental model for interacting with ACC in real conditions. Research questions aimed to model the learning process in mathematical/statistical terms, examine moments and conditions when these processes stabilize, and assess how experience changes the mental model of the system. A sample of fifteen drivers without ACC experience drove a test vehicle with ACC ten consecutive times on the same route within a 2-month period. In contrast to the driving simulator study, all participants were fully trained in ACC functionality by reading the owner’s manual in the beginning. Results showed that learning, as well as the development of acceptance and trust in ACC follows the power law of learning, in case of comprehensive prior information on system limitations. Thus, the major part of the learning process occurred during the first interaction with the system and support in explaining the systems abilities (e.g. by tutoring systems) should therefore primarily be given during this first stage. All processes stabilized at a relatively high level after the fifth session, which corresponds to 185 km or 3.5 hours of driving. No decline was observable with ongoing system experience. However, in line with the findings from the simulator study, limitations that are not experienced tended to disappear from the mental model if they were not activated by experience. With regard to the validation of the developed methods for assessing mental models and SA, results are encouraging. The studies show that the mental model questionnaire is able to provide insights into the construction of mental models and the development over time. Likewise, the implicit measurement approach to assess SA online in the driving simulator is sensitive to user’s awareness of potentially critical situations. In terms of content, the results of the studies prove the enduring relevance of the initial mental model for the learning process, SA, as well as the development of trust, acceptance and a realistic mental model about automation capabilities and limitations. Given the importance of the initial mental model it is recommended that studies on system trust and acceptance should include, and attempt to control, users’ initial mental model of system functionality. Although the results showed that also incorrect and incomplete initial mental models converged by experience towards a realistic appreciation of system functionality, the more cognitive effort needed to update the mental model, the lower trust and acceptance. Providing an idealised description, which omits potential problems, only leads to temporarily higher trust and acceptance in the beginning. The experience of unexpected limitations results in a steady decrease in trust and acceptance over time. A trial-and-error strategy for in-vehicle automation use, without accompanying information, is therefore considered insufficient for developing stable trust and acceptance. If the mental model matches experience, trust and acceptance grow steadily following the power law of learning – regardless of the experience of system limitations. Provided that such events are known in advance, they will not cause a decrease in trust and acceptance over time. Even over-information about potential problems lowers trust and acceptance only in the beginning, and not in the long run. Potential problems should therefore not be concealed in over-idealised system descriptions; the more information given, the better, in the long run. However, limitations that are not experienced tend to disappear from the mental model. Therefore, it is recommended that users be periodically reminded of system limitations to make sure that corresponding knowledge becomes re-activated. Intelligent tutoring systems incorporated in automated systems could provide a solution. In the driving context, periodic reminders about system limitations could be shown via the multifunction displays integrated in most modern cars. Tutoring systems could also be used to remind the driver of the presence of specific in-vehicle automation systems and reveal their benefits
Viele Aufgaben, die ehemals von Menschen ausgeführt wurden, werden heute von Maschinen übernommen. Dieser Prozess der Automatisierung betrifft viele Lebensbereiche von Arbeit, Wohnen, Kommunikation bis hin zur Mobilität. Im Bereich des Individualverkehrs wird die Automatisierung von Fahrzeugen als Möglichkeit gesehen, zukünftigen Herausforderungen wirtschaftlicher, gesellschaftlicher und umweltpolitischer Art zu begegnen. Allerdings verändert Automatisierung die Fahraufgabe und die Mensch-Technik Interaktion im Fahrzeug. Daher können beispielsweise erwartete Sicherheitsgewinne automatisch agierender Assistenzsysteme durch Veränderungen im Verhalten des Fahrers geschmälert werden, was als Verhaltensanpassung (behavioural adaptation) bezeichnet wird. Dieses Dissertationsprojekt untersucht motivationale und höhere kognitive Prozesse, die Verhaltensanpassungen im Umgang mit automatisierten Fahrerassistenzsystemen zugrunde liegen. Motivationale Prozesse beinhalten die Entwicklung von Akzeptanz und Vertrauen in das System, unter höheren kognitiven Prozessen werden Lernprozesse sowie die Entwicklung von mentalen Modellen des Systems und Situationsbewusstsein (Situation Awareness) verstanden. Im Fokus der Untersuchungen steht das Fahrerassistenzsystem Adaptive Cruise Control (ACC) als ein Beispiel für Automatisierung im Fahrzeug. ACC regelt automatisch die Geschwindigkeit des Fahrzeugs, indem bei freier Fahrbahn eine eingestellte Wunschgeschwindigkeit und bei einem Vorausfahrer automatisch ein eingestellter Abstand eingehalten wird. Allerdings kann ACC aufgrund von Einschränkungen der Sensorik nicht jede Situation bewältigen, weshalb der Fahrer übernehmen muss. Für diesen Interaktionsprozess spielen Vertrauen, Akzeptanz und das mentale Modell der Systemfunktionalität eine Schlüsselrolle, um einen sicheren Umgang mit dem System und ein adäquates Situationsbewusstsein zu entwickeln. Zur systematischen Erforschung dieser motivationalen und kognitiven Prozesse wurden eine Fahrsimulatorstudie und ein Versuch im Realverkehr durchgeführt. Beide Studien wurden im Messwiederholungsdesign angelegt, um dem Prozesscharakter gerecht werden und Veränderungen über die Zeit erfassen zu können. Die Entwicklung von Vertrauen, Akzeptanz und mentalem Modell in der Interaktion mit ACC war zentraler Forschungsgegenstand beider Studien. Bislang gibt es wenige Studien, die kognitive Prozesse im Kontext der Fahrzeugführung untersucht haben, unter anderem auch wegen methodischer Schwierigkeiten in diesem dynamischen Umfeld. Daher war es ebenfalls Teil dieses Dissertationsprojekts, neue Methoden zur Erfassung höherer kognitiver Prozesse in dieser Domäne zu entwickeln, mit Fokus auf mentalen Modellen und Situationsbewusstsein. Darüber hinaus wurde auch ein neuer Ansatz für die Analyse großer und heterogener Datenmengen im sozialwissenschaftlichen Bereich entwickelt, basierend auf dem Einsatz relationaler Datenbanken. Ziel der der Fahrsimulatorstudie war die systematische Erforschung des Effekts von unterschiedlich korrekten initialen mentalen Modellen von ACC auf die weitere Entwicklung des mentalen Modells, Vertrauen und Akzeptanz des Systems. Eine Stichprobe von insgesamt 51 Probanden nahm an der Studie teil; der Versuch wurde als zweifaktorielles (3x3) gemischtes Messwiederholungsdesign konzipiert. Die 3 parallelisierten Versuchsgruppen zu je 17 Personen erhielten (1) eine korrekte Beschreibung des ACC, (2) eine idealisierte Beschreibung unter Auslassung auftretender Systemprobleme und (3) eine überkritische Beschreibung mit zusätzlichen Hinweisen auf Systemprobleme, die nie auftraten. Alle Teilnehmer befuhren insgesamt dreimal im Zeitraum von sechs Wochen dieselbe 56 km lange Autobahnstrecke im Fahrsimulator mit identischem ACC-System. Mit zunehmendem Einsatz des ACC zeigte sich im anfänglich divergierenden mentalen Modell zwischen den Gruppen eine Entwicklung hin zum mentalen Modell der korrekt informierten Gruppe. Nicht erfahrene Systemprobleme tendierten dazu, im mentalen Modell zu verblassen, wenn sie nicht durch Erfahrung reaktiviert wurden. Vertrauen und Akzeptanz stiegen stetig in der korrekt informierten Gruppe. Dieselbe Entwicklung zeigte sich auch in der überkritisch informierten Gruppe, wobei Vertrauen und Akzeptanz anfänglich niedriger waren als in der Bedingung mit korrekter Information. Verschwiegene Systemprobleme führten zu einer konstanten Abnahme von Akzeptanz und Vertrauen ohne Erholung in der Gruppe mit idealisierter Beschreibung. Diese Resultate lassen darauf schließen, dass Probleme automatisierter Systeme sich nicht zwingend negativ auf Vertrauen und Akzeptanz auswirken, sofern sie vorab bekannt sind. Bei jeder Fahrt führten die Versuchsteilnehmer zudem kontinuierlich eine visuell beanspruchende Zweitaufgabe aus, die Surrogate Reference Task (SURT). Die Frequenz der Zweitaufgabenbearbeitung diente als objektives Echtzeitmaß für das Situationsbewusstsein, basierend auf dem Ansatz, dass situationsbewusste Fahrer die Zuwendung zur Zweitaufgabe reduzieren wenn sie potentiell kritische Situationen erwarten. Die Ergebnisse zeigten, dass die korrekt informierten Fahrer sich potentiell kritischer Situationen mit möglichen Systemproblemen bewusst waren und schon im Vorfeld der Entstehung die Zweitaufgabenbearbeitung reduzierten. Teilnehmer ohne Informationen zu auftretenden Systemproblemen wurden sich solcher Situationen erst nach dem ersten Auftreten bewusst und reduzierten in entsprechenden Szenarien der Folgefahrten die Zweitaufgabenbearbeitung. Allerdings sanken Vertrauen und Akzeptanz des Systems aufgrund der unerwarteten Probleme. Erwartete, aber nicht auftretende Systemprobleme tendierten dazu, im mentalen Modell des Systems zu verblassen und resultierten in vermindertem Situationsbewusstsein bereits in der zweiten Fahrt. Im Versuch unter Realbedingungen wurden der Lernprozesses sowie die Entwicklung des mentalen Modells, Vertrauen und Akzeptanz von ACC im Realverkehr erforscht. Ziele waren die statistisch/mathematische Modellierung des Lernprozesses, die Bestimmung von Zeitpunkten der Stabilisierung dieser Prozesse und wie sich reale Systemerfahrung auf das mentale Modell von ACC auswirkt. 15 Versuchsteilnehmer ohne ACC-Erfahrung fuhren ein Serienfahrzeug mit ACC insgesamt 10-mal auf der gleichen Strecke in einem Zeitraum von 2 Monaten. Im Unterschied zur Fahrsimulatorstudie waren alle Teilnehmer korrekt über die ACC-Funktionen und Funktionsgrenzen informiert durch Lesen der entsprechenden Abschnitte im Fahrzeughandbuch am Beginn der Studie. Die Ergebnisse zeigten, dass der Lernprozess sowie die Entwicklung von Akzeptanz und Vertrauen einer klassischen Lernkurve folgen – unter der Bedingung umfassender vorheriger Information zu Systemgrenzen. Der größte Lernfortschritt ist am Beginn der Interaktion mit dem System sichtbar und daher sollten Hilfen (z.B. durch intelligente Tutorsysteme) in erster Linie zu diesem Zeitpunkt gegeben werden. Eine Stabilisierung aller Prozesse zeigte sich nach der fünften Fahrt, was einer Fahrstrecke von rund 185 km oder 3,5 Stunden Fahrzeit entspricht. Es zeigten sich keine Einbrüche in Akzeptanz, Vertrauen bzw. dem Lernprozess durch die gemachten Erfahrungen im Straßenverkehr. Allerdings zeigte sich – analog zur Fahrsimulatorstudie – auch in der Realfahrstudie ein Verblassen von nicht erfahrenen Systemgrenzen im mentalen Modell, wenn diese nicht durch Erfahrungen aktiviert wurden. Im Hinblick auf die Validierung der neu entwickelten Methoden zur Erfassung von mentalen Modellen und Situationsbewusstsein sind die Resultate vielversprechend. Die Studien zeigen, dass mit dem entwickelten Fragebogenansatz zur Quantifizierung des mentalen Modells Einblicke in Aufbau und Entwicklung mentaler Modelle gegeben werden können. Der implizite Echtzeit-Messansatz für Situationsbewusstsein im Fahrsimulator zeigt sich ebenfalls sensitiv in der Erfassung des Bewusstseins von Fahrern für potentiell kritische Situationen. Inhaltlich zeigen die Studien die nachhaltige Relevanz des initialen mentalen Modells für den Lernprozess sowie die Entwicklung von Situationsbewusstsein, Akzeptanz, Vertrauen und die weitere Ausformung eines realistischen mentalen Modells der Möglichkeiten und Grenzen automatisierter Systeme. Aufgrund dieser Relevanz wird die Einbindung und Kontrolle des initialen mentalen Modells in Studien zu automatisierten Systemen unbedingt empfohlen. Die Ergebnisse zeigen zwar, dass sich auch unvollständige bzw. falsche mentale Modelle durch Erfahrungslernen hin zu einer realistischen Einschätzung der Systemmöglichkeiten und -grenzen verändern, allerdings um den Preis sinkenden Vertrauens und abnehmender Akzeptanz. Idealisierte Systembeschreibungen ohne Hinweise auf mögliche Systemprobleme bringen nur anfänglich etwas höheres Vertrauen und Akzeptanz. Das Erleben unerwarteter Probleme führt zu einem stetigen Abfall dieser motivationalen Faktoren über die Zeit. Ein alleiniges Versuchs-Irrtums-Lernen für den Umgang mit automatisierter Assistenz im Fahrzeug ohne zusätzliche Information wird daher als nicht ausreichend für die Entwicklung stabilen Vertrauens und stabiler Akzeptanz betrachtet. Wenn das initiale mentale Modell den Erfahrungen entspricht, entwickeln sich Akzeptanz und Vertrauen gemäß einer klassischen Lernkurve – trotz erlebter Systemgrenzen. Sind diese potentiellen Probleme vorher bekannt, führen sie nicht zwingend zu einer Reduktion von Vertrauen und Akzeptanz. Auch zusätzliche überkritische Information vermindert Vertrauen und Akzeptanz nur am Beginn, aber nicht langfristig. Daher sollen potentielle Probleme in automatisierten Systemen nicht in idealisierten Beschreibungen verschwiegen werden – je präzisere Information gegeben wird, desto besser im langfristigen Verlauf. Allerdings tendieren nicht erfahrene Systemgrenzen zum Verblassen im mentalen Modell. Daher wird empfohlen, Nutzer regelmäßig an diese Systemgrenzen zu erinnern um die entsprechenden Facetten des mentalen Modells zu reaktivieren. In automatisierten Systemen integrierte intelligente Tutorsysteme könnten dafür eine Lösung bieten. Im Fahrzeugbereich könnten solche periodischen Erinnerungen an Systemgrenzen in Multifunktionsdisplays angezeigt werden, die mittlerweile in vielen modernen Fahrzeugen integriert sind. Diese Tutorsysteme können darüber hinaus auch auf die Präsenz eingebauter automatisierter Systeme hinweisen und deren Vorteile aufzeigen

碩士
國立臺灣師範大學
科學教育研究所
104
The purpose of this study is to explore the dry-ice-themed Scientific Experiment Teaching, which is a combination of PDEODE teaching strategy and ARCS Model of motivational design. This instruction has impacts on students’ achievement while learning science, students’ misconception of dry ice and students’ emotional quality while conducting learning tasks. The mixed method study is conducted using quantitative method and qualitative data. The subject of the study is high school freshmen, in whom they are divided into two groups: 47 students were implemented in the PDEODE strategy and ARCS model experimental group; whereas 41 students were implemented in conventional teaching control group. All subjects were given Dry Ice Concept pre-and post-test, while only the experimental group were given the Chemistry Experiment Interest Inventory. The data sources of this study were Dry Ice Concept pre- and post-test, PDEODE learning sheets, measures on the Chemistry Experiment Interest Inventory and transcribed interviews. Quantitative data was analysed using ANCOVA and ANOVA. The results of the study indicate that (a)The achievement of students in the experimental group is higher than those students in the traditional teaching group. (b)The students in the experimental group tend to be more positive in emotional quality while conducting learning tasks, and they have higher learning achievements. (c)The combined form of ARCS model and course design structure will bring effect on students' learning concept. Some suggestions are made according to the results of study: (a)Avoid giving more complex concepts to students for them to predict during activities, so the students will not lost interest while making guesses recklessly. (b)Make sure the students are assigned with hands-on experiments that are arranged accordingly based on difficulties. (c)Schedule adequate time for students’ group discussion so they have sufficient time to avoid conceptual conflict among members. (d)Educators shall constantly patrol the groups when students are given learning tasks. Encourage the students to verbally express and lead the activities more frequently. Based on given suggestions, the researchers hope that ARCS-PDEODE instruction can be well-developed for the students in high school junior year so that they can have better fundamental knowledge in science through the learning strategy.

碩士
國立臺北科技大學
技術及職業教育研究所
106
The paper is aimed to study the effects of ARCS motivational model applying on “the All-out Defense Education” on vocational students and learning performance. Due to the fact that the All-out Defense Education in senior high schools nowadays is not been considered as a major subject, students are not as motivated to learn All-out Defense as to the rest of subjects. The interviewees of this study were made up by two classes of students from the department of automobile technique, including 47 students in experimental group and 42 students in control group.The statistical application this study used was SPSS. The empirical data showed that experimental group is significantly performed better on learning performance than the control group which remained unchanged. In addition the experimental group led a significant result over the control groups. It means the ARCS motivational model could enhance students’ interests in learning All-out Defense Education. However in regard to the curriculum design of normal senior high schools, the All-out Defense Education is an elective course. It is suggested to future research could examine how the ARCS model works in the required curriculum of All-out Defense Education.of senior high schools.

碩士
國立中山大學
資訊管理學系研究所
99
Although many researchers have pointed out that educational robots can motivate student learning, learning motivation inevitably declines over time. The sustainability of learning motivation is closely related to instructional strategies. In other words, appropriate instructional strategies are still essential to sustain a learner''s learning motivation in robot-assisted instructions. The ARCS model provides systematic guidelines for enhancing and sustaining learning motivation; however, it provides very limited instructional practices in the model. Recent development in educational robot grows rapidly. A humanoid robot, which has a tangible and attractive body and limbs, is able to perform movements and gestures and to interact with its users. This study aims to develop instructional strategies and activities based on the ARCS model and the specific features of the robot teaching assistant (RTA) to enhance and sustain motivation in learning English reading skills. A quasi experiment and a survey were conducted to evaluate the effects of the designed strategies and activities. The results showed that the design of the RTA-based activities following the ARCS model for learning English reading skills was positively and significantly contributed to students’ learning motivation, learning performance and continuance intention.

碩士
國立臺北教育大學
教育傳播與科技研究所
106
The study aimed to design and develop multimedia teaching materials of environmental education for elementary school senior students. The design resolved the difficulty of teachers in teaching environmental education, and discussed the problems during the development of multimedia teaching material and whether if the teaching materials of development met the teachers’ requirement and students’ Learning. Through literature review and interview with six teachers of related fields, the paper attempted to understand the difficulty of teaching environmental education courses and actual demand of teachers, and designed and developed teaching materials based on the design principles of multimedia material and ARCS motivation model. The developing process referred to ADDIE model, has been divided into 5 stages: the analysis stage, design stage, development stage, implementation stage and evaluation stage, designed four units in content of environmental education curriculum for water resources and carbon reduction. The paper conducted formative evaluation materials through the scale and interviewed teachers to discuss whether if the course met the teaching requirement and the teachers' satisfaction with teaching materials. Finally, two teachers used material at the teaching site and discussed about the learning effectiveness of 24 fifth graders and 18 sixth graders. The study results are shown in the follows: 1.The development of multimedia teaching materials for elementary school environmental education is required and necessary due to the insufficiency of existing teaching material and the teaching requirement. 2.The induced seven multimedia design principles combined with ARCS motivation model of developing multimedia materials for environmental education included: (1) Designing a playful interface. (2) Set up clear learning focus and goals. (3) Providing film or image of thinking issues. (4) Designing lifestyle of the discussion topics. (5) Providing practice opportunities for interactive quizzes. (6) Providing instant feedback function. (7) Designing simple and interactive user interface. 3.The multimedia teaching materials developed from the induced design principles met the teaching requirement from teachers of related fields. 4.Teachers used the multimedia materials which developed from this study for teaching to effectively enhanced students' learning outcomes.

abstract: This study empirically evaluated the effectiveness of the instructional design, learning tools, and role of the teacher in three versions of a semester-long, high-school remedial Algebra I course to determine what impact self-regulated learning skills and learning pattern training have on students' self-regulation, math achievement, and motivation. The 1st version was a business-as-usual traditional classroom teaching mathematics with direct instruction. The 2rd version of the course provided students with self-paced, individualized Algebra instruction with a web-based, intelligent tutor. The 3rd version of the course coupled self-paced, individualized instruction on the web-based, intelligent Algebra tutor coupled with a series of e-learning modules on self-regulated learning knowledge and skills that were distributed throughout the semester. A quasi-experimental, mixed methods evaluation design was used by assigning pre-registered, high-school remedial Algebra I class periods made up of an approximately equal number of students to one of the three study conditions or course versions: (a) the control course design, (b) web-based, intelligent tutor only course design, and (c) web-based, intelligent tutor + SRL e-learning modules course design. While no statistically significant differences on SRL skills, math achievement or motivation were found between the three conditions, effect-size estimates provide suggestive evidence that using the SRL e-learning modules based on ARCS motivation model (Keller, 2010) and Let Me Learn learning pattern instruction (Dawkins, Kottkamp, & Johnston, 2010) may help students regulate their learning and improve their study skills while using a web-based, intelligent Algebra tutor as evidenced by positive impacts on math achievement, motivation, and self-regulated learning skills. The study also explored predictive analyses using multiple regression and found that predictive models based on independent variables aligned to student demographics, learning mastery skills, and ARCS motivational factors are helpful in defining how to further refine course design and design learning evaluations that measure achievement, motivation, and self-regulated learning in web-based learning environments, including intelligent tutoring systems.
Dissertation/Thesis
Ph.D. Educational Technology 2013

碩士
國立中山大學
教育研究所
98
The purpose of this study was, based on Keller’s ARCS motivational model, to develop and design feasible instruction in order to improve college students’ motivation to learn and achievement toward information technology and society course. Participants were 220 college students from four classes and two teachers in a technical and vocational college. Each teacher taught two classes, and every teacher was randomly assigned to one experimental group and one control group from those two classes. Data was collected through the administration of Learning Motivation Inventory (LMI) which was developed by the researcher. In addition, students’ midterm and final exam scores were collected. The collected data was analyzed by using the statistical methods of t-test, One-Way ANOVA, and Pearson Product-Moment Correlation. The conclusions of this study are as follows: 1. There was no significant relationship between students’ motivation to learn and achievement. 2. There was no significant difference on students’ motivation to learn of experimental group and control group. 3. There was no significant difference on students’ achievement of experimental group and control group. Although the results had no significant difference between the two groups. The researcher reviewed the instructional design during courses, and also addressed the status quo for these students’ learning situation. Based on the above conclusions, this research proposed concrete suggestions for educators to promote technical and vocational college students’ motivation to learn and achievement.

碩士
國立臺北教育大學
教育傳播與科技研究所
98
Since 2002, Executive Yuan had planned to promote the project named as National Digital Archive Program(NDAP). It is believed that digital archives materials are useful resources to assist teaching for education.Hence, the teacher must know how to adopt the proper teaching strategies with digital archives to perform well and efficiently. Therefore, this study is based on digital archives and the Keller's ARCS motivation model to design the teaching of traditional opera “Chinese Opera Unit”on the Art and Humanist Curriculum in junior high school. The purpose of this study is to understand the influences of the effects on learning motivation and effectiveness among junior high school students by teaching. This study adopts quasi-experimental research to see how it affect the eighth-grade junior high school students. The quantititive data is gathered from questionnaires of learning motivation and learning achievement. This study gather the qualitative data by interviewing to analyze both the opinions of students and teachers for further understanding. Finally the suggestions is made according to the results of this research as a reference for future instruction or research. The main findings are as follows: 1.The teaching with digital archives has significant effect to learning motivation. And, the teaching with ARCS Motivation Model has significant effect to learning motivation. With regard to learning motivation, students who accept the teaching with digital archives is better than without digital archives, and students who accept the teaching with ARCS Motivation Model is better than without ARCS Motivation Model. 2.The teaching with digital archives has significant effect of learning achievement. With regard to learning achievement, students who accept the teaching with digital archives is better than without digital archives materials. 3.Students who have the different experiences on internet using do not have significant effect to learning motivation. 4.Students who have the different degree of Chinese Opera preference and learning achievement of the Art and Humanist Curriculum have significant effect to learning motivation. The higher degree of Chinese Opera preference and learning achievement of the Art and Humanist Curriculum the students have, the better the students are in their learning motivation. 5.The teacher and most students are positive in their conception of the traditional opera teaching with digital archives and ARCS motivation model, both of learning motivation and achievement can be improved.

To be successful, social network sites need continual activity to flourish and grow. One of the most important challenges faced by designers of social network sites, is to encourage contribution from community members. ‘Self-sustainability’ is critical to the survival of networked communities and is dependent on community members adding content in a sustained way over time. Motivating community members to take it upon themselves to freely contribute information is the key to the success of any social network environment (Powazek, 2002; Ling et al., 2005). This thesis aims to investigate whether persuasion techniques can be used to inform the design process in order to motivate members of a social network community to contribute content. While persuasion theories have been effective in influencing target behaviour outside of the online environment, traditionally they have not been utilised by digital media designers. With the advent of social media, the application of social psychology is becoming more valuable in the development of features and strategies for the online environment. Recently the field of Captology has begun to systematically investigate computers as persuasive technology. Within this field, this thesis has investigated using the ‘Elaboration Likelihood Model’ (ELM) as a strategic framework and ‘Social Proof’ as a motivating influence to develop peripheral elements designed to encourage user online contribution, and to design a site that is visually appealing and functional. This is essential in establishing the credibility of the site without which the influences of persuasion are unable to function. This Masters ‘research through design’ project engages an existing community group of water sports enthusiasts in a trial of a live prototype website. The website was designed to utilise the internet as a medium and social networking as a tool, in order to gather individual knowledge, give it a context, and to create a self-sustaining collective knowledge base of locations, optimum conditions and user experiences. Users were divided randomly into two groups – the test and the control. Using ELM, the peripheral and central routes of processing communication were identified, and used to build the framework on which to develop the test environment. Both groups were exposed to the same fundamental design and functionality, however the test group was presented with additional peripheral elements designed using the principles of Social Proof. The research charted user contributions over the course of 82 days, with a survey undertaken with both groups at the completion of the test period. Results indicated a significant difference between the two test groups with users exposed to the influences of Social Proof more motivated to contribute content and visit the website more often than users from the control group. The findings of this study show that motivating contribution can be achieved using ELM and Social Proof to design persuasive elements in a social networking environment. The synthesis of graphic design, interface design and the theories of social science can guide designers in the creative process of developing networked environments for social media, and lead to a more engaging user experience.

Many functions that at one time could only be performed by humans can nowadays be carried out by machines. Automation impacts many areas of life including work, home, communication and mobility. In the driving context, in-vehicle automation is considered to provide solutions for environmental, economic, safety and societal challenges. However, automation changes the driving task and the human-machine interaction. Thus, the expected benefit of in-vehicle automation can be undermined by changes in drivers’ behaviour, i.e. behavioural adaptation. This PhD project focuses on motivational as well as higher cognitive processes underlying behavioural adaptation when interacting with in-vehicle automation. Motivational processes include the development of trust and acceptance, whereas higher cognitive processes comprise the learning process as well as the development of mental models and Situation Awareness (SA). As an example for in-vehicle automation, the advanced driver assistance system Adaptive Cruise Control (ACC) was investigated. ACC automates speed and distance control by maintaining a constant set cruising speed and automatically adjusting vehicle’s velocity in order to provide a specified distance to the preceding vehicle. However, due to sensor limitations, not every situation can be handled by the system and therefore driver intervention is required. Trust, acceptance and an appropriate mental model of the system functionality are considered key variables for adequate use and appropriate SA. To systematically investigate changes in motivational and higher cognitive processes, a driving simulator as well as an on-road study were carried out. Both of the studies were conducted using a repeated-measures design, taking into account the process character, i.e. changes over time. The main focus was on the development of trust, acceptance and the mental model of novice users when interacting with ACC. By now, only few studies have attempted to assess changes in higher level cognitive processes, due to methodological difficulties posed by the dynamic task of driving. Therefore, this PhD project aimed at the elaboration and validation of innovative methods for assessing higher cognitive processes, with an emphasis on SA and mental models. In addition, a new approach for analyzing big and heterogeneous data in social science was developed, based on the use of relational databases. The driving simulator study investigated the effect of divergent initial mental models of ACC (i.e., varying according to correctness) on trust, acceptance and mental model evolvement. A longitudinal study design was applied, using a two-way (3×3) repeated measures mixed design with a matched sample of 51 subjects. Three experimental groups received (1) a correct ACC description, (2) an incomplete and idealised account omitting potential problems, and (3) an incorrect description including non-occurring problems. All subjects drove a 56-km track of highway with an identical ACC system, three times, and within a period of 6 weeks. Results showed that after using the system, participants’ mental model of ACC converged towards the profile of the correct group. Non-experienced problems tended to disappear from the mental model network when they were not activated by experience. Trust and acceptance grew steadily for the correct condition. The same trend was observed for the group with non-occurring problems, starting from a lower initial level. Omitted problems in the incomplete group led to a constant decrease in trust and acceptance without recovery. This indicates that automation failures do not negatively affect trust and acceptance if they are known beforehand. During each drive, participants continuously completed a visual secondary task, the Surrogate Reference Task (SURT). The frequency of task completion was used as objective online-measure for SA, based on the principle that situationally aware driver would reduce the engagement in the secondary task if they expect potentially critical situations. Results showed that correctly informed drivers were aware of potential system limitations and reduced their engagement in the secondary task when such situations arose. Participants with no information about limitations became only aware after first encounter and reduced secondary task engagement in corresponding situations during subsequent trials. However, trust and acceptance in the system declined over time due to the unexpected failures. Non occurring limitations tended to drop from the mental model and resulted in reduced SA already in the second trial. The on-road study investigated the learning process, as well as the development of trust, acceptance and the mental model for interacting with ACC in real conditions. Research questions aimed to model the learning process in mathematical/statistical terms, examine moments and conditions when these processes stabilize, and assess how experience changes the mental model of the system. A sample of fifteen drivers without ACC experience drove a test vehicle with ACC ten consecutive times on the same route within a 2-month period. In contrast to the driving simulator study, all participants were fully trained in ACC functionality by reading the owner’s manual in the beginning. Results showed that learning, as well as the development of acceptance and trust in ACC follows the power law of learning, in case of comprehensive prior information on system limitations. Thus, the major part of the learning process occurred during the first interaction with the system and support in explaining the systems abilities (e.g. by tutoring systems) should therefore primarily be given during this first stage. All processes stabilized at a relatively high level after the fifth session, which corresponds to 185 km or 3.5 hours of driving. No decline was observable with ongoing system experience. However, in line with the findings from the simulator study, limitations that are not experienced tended to disappear from the mental model if they were not activated by experience. With regard to the validation of the developed methods for assessing mental models and SA, results are encouraging. The studies show that the mental model questionnaire is able to provide insights into the construction of mental models and the development over time. Likewise, the implicit measurement approach to assess SA online in the driving simulator is sensitive to user’s awareness of potentially critical situations. In terms of content, the results of the studies prove the enduring relevance of the initial mental model for the learning process, SA, as well as the development of trust, acceptance and a realistic mental model about automation capabilities and limitations. Given the importance of the initial mental model it is recommended that studies on system trust and acceptance should include, and attempt to control, users’ initial mental model of system functionality. Although the results showed that also incorrect and incomplete initial mental models converged by experience towards a realistic appreciation of system functionality, the more cognitive effort needed to update the mental model, the lower trust and acceptance. Providing an idealised description, which omits potential problems, only leads to temporarily higher trust and acceptance in the beginning. The experience of unexpected limitations results in a steady decrease in trust and acceptance over time. A trial-and-error strategy for in-vehicle automation use, without accompanying information, is therefore considered insufficient for developing stable trust and acceptance. If the mental model matches experience, trust and acceptance grow steadily following the power law of learning – regardless of the experience of system limitations. Provided that such events are known in advance, they will not cause a decrease in trust and acceptance over time. Even over-information about potential problems lowers trust and acceptance only in the beginning, and not in the long run. Potential problems should therefore not be concealed in over-idealised system descriptions; the more information given, the better, in the long run. However, limitations that are not experienced tend to disappear from the mental model. Therefore, it is recommended that users be periodically reminded of system limitations to make sure that corresponding knowledge becomes re-activated. Intelligent tutoring systems incorporated in automated systems could provide a solution. In the driving context, periodic reminders about system limitations could be shown via the multifunction displays integrated in most modern cars. Tutoring systems could also be used to remind the driver of the presence of specific in-vehicle automation systems and reveal their benefits.:Table of contents LIST OF FIGURES I LIST OF TABLES II LIST OF ABBREVIATIONS III ACKNOWLEDGEMENTS IV SUMMARY V ZUSAMMENFASSUNG VIII 1 INTRODUCTION 12 2 THEORETICAL BACKGROUND 14 2.1 BEHAVIOURAL ADAPTATION AND HIGHER COGNITIVE PROCESSES 14 2.2 VEHICLE AUTOMATION AND ADAPTIVE CRUISE CONTROL 17 2.3 MENTAL MODELS 20 2.3.1 Definition 20 2.3.2 Mental model construction and update 20 2.3.3 Discussion of existing measures 21 2.3.4 Development of the mental model questionnaire 23 2.4 SITUATION AWARENESS 24 2.4.1 Definition 24 2.4.2 Relationship between mental models and Situation Awareness 26 2.4.3 Situation Awareness as comprehension process 27 2.4.4 Discussion of existing measures 27 2.4.5 Development of the Situation Awareness measurement technique 29 2.5 LEARNING, ACCEPTANCE AND TRUST IN AUTOMATION 30 2.5.1 Power law of learning 30 2.5.2 Acceptance 31 2.5.3 Trust in automation 31 2.5.4 Related research on learning, acceptance and trust in ACC 32 3 OVERALL RESEARCH QUESTIONS 34 4 OVERALL METHODOLOGICAL CONSIDERATIONS 35 4.1 DRIVING SIMULATOR STUDIES AND ON-ROAD TESTS 35 4.2 DATABASE-FRAMEWORK FOR DATA STORAGE AND ANALYSIS 37 5 DRIVING SIMULATOR STUDY 42 5.1 AIMS AND RESEARCH QUESTIONS 42 5.2 METHOD AND MATERIAL 43 5.2.1 Sampling and participants 43 5.2.2 Research design and procedure 44 5.2.3 Facilities and driving simulator track 45 5.2.4 Secondary task SURT 46 5.2.5 System description 46 5.2.6 Dependent variables trust, acceptance and mental model 47 5.2.7 Contrast analysis 48 5.3 RESULTS 49 5.3.1 Mental model 49 5.3.2 Trust and acceptance 51 5.3.3 Situation Awareness 52 5.4 DISCUSSION 56 6 ON-ROAD STUDY 59 6.1 AIMS AND RESEARCH QUESTIONS 59 6.2 METHOD AND MATERIAL 59 6.2.1 Research design and procedure 59 6.2.2 Sampling and participants 60 6.2.3 Facilities and apparatus 60 6.2.4 Dependent variables mental model, trust, acceptance, learning and ACC usage 62 6.3 RESULTS 63 6.3.1 ACC usage 63 6.3.2 Trust and acceptance 64 6.3.3 Learning 65 6.3.4 Mental model 67 6.4 DISCUSSION 68 7 GENERAL DISCUSSION AND CONCLUSIONS 70 7.1 THEORETICAL AND PRACTICAL CONSIDERATIONS 70 7.2 METHODOLOGICAL CONSIDERATIONS 71 7.3 LIMITATIONS AND DIRECTIONS FOR FUTURE RESEARCH 74 8 REFERENCES 76 9 APPENDIX 88 9.1 QUESTIONNAIRES USED IN THE DRIVING SIMULATOR STUDY 88 9.1.1 Original German version 88 9.1.2 English translation 91 9.2 ACC DESCRIPTIONS USED IN THE DRIVING SIMULATOR STUDY 94 9.2.1 Correct description 94 9.2.2 Incomplete description 95 9.2.3 Incorrect description 96 9.3 SCHEMATIC OVERVIEW OF THE DRIVING SIMULATOR TRACK 97 9.4 QUESTIONNAIRES USED IN THE ON-ROAD STUDY 99 9.4.1 Original German version 99 9.4.2 English translation 103 9.5 SEMINAR PROGRAMME: DATABASES AS ANALYSIS TOOL IN SOCIAL SCIENCE 107 9.6 CURRICULUM VITAE AND PUBLICATIONS 109
Viele Aufgaben, die ehemals von Menschen ausgeführt wurden, werden heute von Maschinen übernommen. Dieser Prozess der Automatisierung betrifft viele Lebensbereiche von Arbeit, Wohnen, Kommunikation bis hin zur Mobilität. Im Bereich des Individualverkehrs wird die Automatisierung von Fahrzeugen als Möglichkeit gesehen, zukünftigen Herausforderungen wirtschaftlicher, gesellschaftlicher und umweltpolitischer Art zu begegnen. Allerdings verändert Automatisierung die Fahraufgabe und die Mensch-Technik Interaktion im Fahrzeug. Daher können beispielsweise erwartete Sicherheitsgewinne automatisch agierender Assistenzsysteme durch Veränderungen im Verhalten des Fahrers geschmälert werden, was als Verhaltensanpassung (behavioural adaptation) bezeichnet wird. Dieses Dissertationsprojekt untersucht motivationale und höhere kognitive Prozesse, die Verhaltensanpassungen im Umgang mit automatisierten Fahrerassistenzsystemen zugrunde liegen. Motivationale Prozesse beinhalten die Entwicklung von Akzeptanz und Vertrauen in das System, unter höheren kognitiven Prozessen werden Lernprozesse sowie die Entwicklung von mentalen Modellen des Systems und Situationsbewusstsein (Situation Awareness) verstanden. Im Fokus der Untersuchungen steht das Fahrerassistenzsystem Adaptive Cruise Control (ACC) als ein Beispiel für Automatisierung im Fahrzeug. ACC regelt automatisch die Geschwindigkeit des Fahrzeugs, indem bei freier Fahrbahn eine eingestellte Wunschgeschwindigkeit und bei einem Vorausfahrer automatisch ein eingestellter Abstand eingehalten wird. Allerdings kann ACC aufgrund von Einschränkungen der Sensorik nicht jede Situation bewältigen, weshalb der Fahrer übernehmen muss. Für diesen Interaktionsprozess spielen Vertrauen, Akzeptanz und das mentale Modell der Systemfunktionalität eine Schlüsselrolle, um einen sicheren Umgang mit dem System und ein adäquates Situationsbewusstsein zu entwickeln. Zur systematischen Erforschung dieser motivationalen und kognitiven Prozesse wurden eine Fahrsimulatorstudie und ein Versuch im Realverkehr durchgeführt. Beide Studien wurden im Messwiederholungsdesign angelegt, um dem Prozesscharakter gerecht werden und Veränderungen über die Zeit erfassen zu können. Die Entwicklung von Vertrauen, Akzeptanz und mentalem Modell in der Interaktion mit ACC war zentraler Forschungsgegenstand beider Studien. Bislang gibt es wenige Studien, die kognitive Prozesse im Kontext der Fahrzeugführung untersucht haben, unter anderem auch wegen methodischer Schwierigkeiten in diesem dynamischen Umfeld. Daher war es ebenfalls Teil dieses Dissertationsprojekts, neue Methoden zur Erfassung höherer kognitiver Prozesse in dieser Domäne zu entwickeln, mit Fokus auf mentalen Modellen und Situationsbewusstsein. Darüber hinaus wurde auch ein neuer Ansatz für die Analyse großer und heterogener Datenmengen im sozialwissenschaftlichen Bereich entwickelt, basierend auf dem Einsatz relationaler Datenbanken. Ziel der der Fahrsimulatorstudie war die systematische Erforschung des Effekts von unterschiedlich korrekten initialen mentalen Modellen von ACC auf die weitere Entwicklung des mentalen Modells, Vertrauen und Akzeptanz des Systems. Eine Stichprobe von insgesamt 51 Probanden nahm an der Studie teil; der Versuch wurde als zweifaktorielles (3x3) gemischtes Messwiederholungsdesign konzipiert. Die 3 parallelisierten Versuchsgruppen zu je 17 Personen erhielten (1) eine korrekte Beschreibung des ACC, (2) eine idealisierte Beschreibung unter Auslassung auftretender Systemprobleme und (3) eine überkritische Beschreibung mit zusätzlichen Hinweisen auf Systemprobleme, die nie auftraten. Alle Teilnehmer befuhren insgesamt dreimal im Zeitraum von sechs Wochen dieselbe 56 km lange Autobahnstrecke im Fahrsimulator mit identischem ACC-System. Mit zunehmendem Einsatz des ACC zeigte sich im anfänglich divergierenden mentalen Modell zwischen den Gruppen eine Entwicklung hin zum mentalen Modell der korrekt informierten Gruppe. Nicht erfahrene Systemprobleme tendierten dazu, im mentalen Modell zu verblassen, wenn sie nicht durch Erfahrung reaktiviert wurden. Vertrauen und Akzeptanz stiegen stetig in der korrekt informierten Gruppe. Dieselbe Entwicklung zeigte sich auch in der überkritisch informierten Gruppe, wobei Vertrauen und Akzeptanz anfänglich niedriger waren als in der Bedingung mit korrekter Information. Verschwiegene Systemprobleme führten zu einer konstanten Abnahme von Akzeptanz und Vertrauen ohne Erholung in der Gruppe mit idealisierter Beschreibung. Diese Resultate lassen darauf schließen, dass Probleme automatisierter Systeme sich nicht zwingend negativ auf Vertrauen und Akzeptanz auswirken, sofern sie vorab bekannt sind. Bei jeder Fahrt führten die Versuchsteilnehmer zudem kontinuierlich eine visuell beanspruchende Zweitaufgabe aus, die Surrogate Reference Task (SURT). Die Frequenz der Zweitaufgabenbearbeitung diente als objektives Echtzeitmaß für das Situationsbewusstsein, basierend auf dem Ansatz, dass situationsbewusste Fahrer die Zuwendung zur Zweitaufgabe reduzieren wenn sie potentiell kritische Situationen erwarten. Die Ergebnisse zeigten, dass die korrekt informierten Fahrer sich potentiell kritischer Situationen mit möglichen Systemproblemen bewusst waren und schon im Vorfeld der Entstehung die Zweitaufgabenbearbeitung reduzierten. Teilnehmer ohne Informationen zu auftretenden Systemproblemen wurden sich solcher Situationen erst nach dem ersten Auftreten bewusst und reduzierten in entsprechenden Szenarien der Folgefahrten die Zweitaufgabenbearbeitung. Allerdings sanken Vertrauen und Akzeptanz des Systems aufgrund der unerwarteten Probleme. Erwartete, aber nicht auftretende Systemprobleme tendierten dazu, im mentalen Modell des Systems zu verblassen und resultierten in vermindertem Situationsbewusstsein bereits in der zweiten Fahrt. Im Versuch unter Realbedingungen wurden der Lernprozesses sowie die Entwicklung des mentalen Modells, Vertrauen und Akzeptanz von ACC im Realverkehr erforscht. Ziele waren die statistisch/mathematische Modellierung des Lernprozesses, die Bestimmung von Zeitpunkten der Stabilisierung dieser Prozesse und wie sich reale Systemerfahrung auf das mentale Modell von ACC auswirkt. 15 Versuchsteilnehmer ohne ACC-Erfahrung fuhren ein Serienfahrzeug mit ACC insgesamt 10-mal auf der gleichen Strecke in einem Zeitraum von 2 Monaten. Im Unterschied zur Fahrsimulatorstudie waren alle Teilnehmer korrekt über die ACC-Funktionen und Funktionsgrenzen informiert durch Lesen der entsprechenden Abschnitte im Fahrzeughandbuch am Beginn der Studie. Die Ergebnisse zeigten, dass der Lernprozess sowie die Entwicklung von Akzeptanz und Vertrauen einer klassischen Lernkurve folgen – unter der Bedingung umfassender vorheriger Information zu Systemgrenzen. Der größte Lernfortschritt ist am Beginn der Interaktion mit dem System sichtbar und daher sollten Hilfen (z.B. durch intelligente Tutorsysteme) in erster Linie zu diesem Zeitpunkt gegeben werden. Eine Stabilisierung aller Prozesse zeigte sich nach der fünften Fahrt, was einer Fahrstrecke von rund 185 km oder 3,5 Stunden Fahrzeit entspricht. Es zeigten sich keine Einbrüche in Akzeptanz, Vertrauen bzw. dem Lernprozess durch die gemachten Erfahrungen im Straßenverkehr. Allerdings zeigte sich – analog zur Fahrsimulatorstudie – auch in der Realfahrstudie ein Verblassen von nicht erfahrenen Systemgrenzen im mentalen Modell, wenn diese nicht durch Erfahrungen aktiviert wurden. Im Hinblick auf die Validierung der neu entwickelten Methoden zur Erfassung von mentalen Modellen und Situationsbewusstsein sind die Resultate vielversprechend. Die Studien zeigen, dass mit dem entwickelten Fragebogenansatz zur Quantifizierung des mentalen Modells Einblicke in Aufbau und Entwicklung mentaler Modelle gegeben werden können. Der implizite Echtzeit-Messansatz für Situationsbewusstsein im Fahrsimulator zeigt sich ebenfalls sensitiv in der Erfassung des Bewusstseins von Fahrern für potentiell kritische Situationen. Inhaltlich zeigen die Studien die nachhaltige Relevanz des initialen mentalen Modells für den Lernprozess sowie die Entwicklung von Situationsbewusstsein, Akzeptanz, Vertrauen und die weitere Ausformung eines realistischen mentalen Modells der Möglichkeiten und Grenzen automatisierter Systeme. Aufgrund dieser Relevanz wird die Einbindung und Kontrolle des initialen mentalen Modells in Studien zu automatisierten Systemen unbedingt empfohlen. Die Ergebnisse zeigen zwar, dass sich auch unvollständige bzw. falsche mentale Modelle durch Erfahrungslernen hin zu einer realistischen Einschätzung der Systemmöglichkeiten und -grenzen verändern, allerdings um den Preis sinkenden Vertrauens und abnehmender Akzeptanz. Idealisierte Systembeschreibungen ohne Hinweise auf mögliche Systemprobleme bringen nur anfänglich etwas höheres Vertrauen und Akzeptanz. Das Erleben unerwarteter Probleme führt zu einem stetigen Abfall dieser motivationalen Faktoren über die Zeit. Ein alleiniges Versuchs-Irrtums-Lernen für den Umgang mit automatisierter Assistenz im Fahrzeug ohne zusätzliche Information wird daher als nicht ausreichend für die Entwicklung stabilen Vertrauens und stabiler Akzeptanz betrachtet. Wenn das initiale mentale Modell den Erfahrungen entspricht, entwickeln sich Akzeptanz und Vertrauen gemäß einer klassischen Lernkurve – trotz erlebter Systemgrenzen. Sind diese potentiellen Probleme vorher bekannt, führen sie nicht zwingend zu einer Reduktion von Vertrauen und Akzeptanz. Auch zusätzliche überkritische Information vermindert Vertrauen und Akzeptanz nur am Beginn, aber nicht langfristig. Daher sollen potentielle Probleme in automatisierten Systemen nicht in idealisierten Beschreibungen verschwiegen werden – je präzisere Information gegeben wird, desto besser im langfristigen Verlauf. Allerdings tendieren nicht erfahrene Systemgrenzen zum Verblassen im mentalen Modell. Daher wird empfohlen, Nutzer regelmäßig an diese Systemgrenzen zu erinnern um die entsprechenden Facetten des mentalen Modells zu reaktivieren. In automatisierten Systemen integrierte intelligente Tutorsysteme könnten dafür eine Lösung bieten. Im Fahrzeugbereich könnten solche periodischen Erinnerungen an Systemgrenzen in Multifunktionsdisplays angezeigt werden, die mittlerweile in vielen modernen Fahrzeugen integriert sind. Diese Tutorsysteme können darüber hinaus auch auf die Präsenz eingebauter automatisierter Systeme hinweisen und deren Vorteile aufzeigen.:Table of contents LIST OF FIGURES I LIST OF TABLES II LIST OF ABBREVIATIONS III ACKNOWLEDGEMENTS IV SUMMARY V ZUSAMMENFASSUNG VIII 1 INTRODUCTION 12 2 THEORETICAL BACKGROUND 14 2.1 BEHAVIOURAL ADAPTATION AND HIGHER COGNITIVE PROCESSES 14 2.2 VEHICLE AUTOMATION AND ADAPTIVE CRUISE CONTROL 17 2.3 MENTAL MODELS 20 2.3.1 Definition 20 2.3.2 Mental model construction and update 20 2.3.3 Discussion of existing measures 21 2.3.4 Development of the mental model questionnaire 23 2.4 SITUATION AWARENESS 24 2.4.1 Definition 24 2.4.2 Relationship between mental models and Situation Awareness 26 2.4.3 Situation Awareness as comprehension process 27 2.4.4 Discussion of existing measures 27 2.4.5 Development of the Situation Awareness measurement technique 29 2.5 LEARNING, ACCEPTANCE AND TRUST IN AUTOMATION 30 2.5.1 Power law of learning 30 2.5.2 Acceptance 31 2.5.3 Trust in automation 31 2.5.4 Related research on learning, acceptance and trust in ACC 32 3 OVERALL RESEARCH QUESTIONS 34 4 OVERALL METHODOLOGICAL CONSIDERATIONS 35 4.1 DRIVING SIMULATOR STUDIES AND ON-ROAD TESTS 35 4.2 DATABASE-FRAMEWORK FOR DATA STORAGE AND ANALYSIS 37 5 DRIVING SIMULATOR STUDY 42 5.1 AIMS AND RESEARCH QUESTIONS 42 5.2 METHOD AND MATERIAL 43 5.2.1 Sampling and participants 43 5.2.2 Research design and procedure 44 5.2.3 Facilities and driving simulator track 45 5.2.4 Secondary task SURT 46 5.2.5 System description 46 5.2.6 Dependent variables trust, acceptance and mental model 47 5.2.7 Contrast analysis 48 5.3 RESULTS 49 5.3.1 Mental model 49 5.3.2 Trust and acceptance 51 5.3.3 Situation Awareness 52 5.4 DISCUSSION 56 6 ON-ROAD STUDY 59 6.1 AIMS AND RESEARCH QUESTIONS 59 6.2 METHOD AND MATERIAL 59 6.2.1 Research design and procedure 59 6.2.2 Sampling and participants 60 6.2.3 Facilities and apparatus 60 6.2.4 Dependent variables mental model, trust, acceptance, learning and ACC usage 62 6.3 RESULTS 63 6.3.1 ACC usage 63 6.3.2 Trust and acceptance 64 6.3.3 Learning 65 6.3.4 Mental model 67 6.4 DISCUSSION 68 7 GENERAL DISCUSSION AND CONCLUSIONS 70 7.1 THEORETICAL AND PRACTICAL CONSIDERATIONS 70 7.2 METHODOLOGICAL CONSIDERATIONS 71 7.3 LIMITATIONS AND DIRECTIONS FOR FUTURE RESEARCH 74 8 REFERENCES 76 9 APPENDIX 88 9.1 QUESTIONNAIRES USED IN THE DRIVING SIMULATOR STUDY 88 9.1.1 Original German version 88 9.1.2 English translation 91 9.2 ACC DESCRIPTIONS USED IN THE DRIVING SIMULATOR STUDY 94 9.2.1 Correct description 94 9.2.2 Incomplete description 95 9.2.3 Incorrect description 96 9.3 SCHEMATIC OVERVIEW OF THE DRIVING SIMULATOR TRACK 97 9.4 QUESTIONNAIRES USED IN THE ON-ROAD STUDY 99 9.4.1 Original German version 99 9.4.2 English translation 103 9.5 SEMINAR PROGRAMME: DATABASES AS ANALYSIS TOOL IN SOCIAL SCIENCE 107 9.6 CURRICULUM VITAE AND PUBLICATIONS 109

A Gestão de Pessoas enaltece o fator humano, o indivíduo e as suas experiências, bem como, o alinhamento entre os objetivos organizacionais com os interesses e as necessidades quer dos indivíduos quer da sociedade. As características do contexto atual constituem desafios para a Gestão de Pessoas, nomeadamente na forma como se trabalha, mais especificamente no desenho das suas funções. Este facto remete-nos para a área do Job Design que se refere ao desenho do trabalho/função que uma pessoa desempenha. O sector da Restauração é um sector crítico e desafiante na área da gestão de pessoas, não só pelas características e natureza do trabalho, como também por absorver mão de obra pouco qualificada, levando a taxas elevadas de turnover. Outro fator desafiante é a tipologia da generalidade das empresas deste setor, PME’s que apresentam falta de estruturas, recursos e conhecimentos para uma gestão de pessoas eficaz e sustentável. A partir destes pressupostos o presente projeto tem como objetivo apresentar uma metodologia de suporte aos diferentes níveis de liderança na gestão de pessoas, de uma empresa do sector da restauração. A empresa pertence a uma Sociedade Gestora de Participação Social (SGPS) que por motivos de confidencialidade não se revela a identidade da Empresa, nem do Grupo. Esta metodologia, pretende potenciar a flexibilização, a humanização e a experiência positiva dos colaboradores, no sentido de aumentar a sua satisfação e motivação no desempenho das suas funções. Para a prossecução do objetivo recorreu-se à metodologia qualitativa de estudo de caso.
In the current context, Human Resource Management praises the human factor, the individual and their experiences, as well as the alignment between organizational objectives with the interests and needs of both individuals and society. On the other hand, the characteristics of the current context represent challenges for Human Resource Management, namely in the way they work, more specifically in the design of functions. This leads us to the Job Design domain, which refers to the design of job or function that a person performs. The Restaurant sector is a critical and challenging sector in Human Resource Management, not only because the characteristics and nature of the work, but also for absorbing low-skilled persons, leading to high turnover rates. On the other hand, most companies in this sector are SMEs with lack of structures, resources and knowledge for effective and sustainable people management. Thus, this project aims to present a methodology to support different levels of leadership in people management, in a company in the restaurant sector. The company belongs to a Social Participation Management Company (SGPS) which, for reasons of confidentiality, will not reveal the identity of the Company or the Group. This methodology aims to enhance the flexibility, humanization, and positive experience of employees, in order to increase their satisfaction and motivation in the performance of their work. For the pursuit of the objective, the qualitative case study methodology was used.