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Journal articles on the topic 'Learning behaviour'

Author: Grafiati

Published: 4 June 2021

Last updated: 20 February 2023

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1

Areche, Franklin Ore. "Students learning Behaviour: Factors influencing Students learning Behavior." International Journal of Language, Literature and Culture 2, no. 3 (2022): 1–11. http://dx.doi.org/10.22161/ijllc.2.3.1.

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The purpose of the research is to identify the relevant aspects that will have a direct impact on students learning behaviour' perceptions of the most popular organized university. The advent of new retailing forms has become considerably more organized and different from traditional retailing forms. The hypothesis is that there is a positive relationship between students learning behaviour, which is a dependent component, and independent factors such as motivation, perception, learning, and attitude, which are independent factors. This paper was analyzed using a quantitative manner. A field survey of students learning behaviourwas conducted in Erbil's various retail university. The data was collected using a random sampling procedure. A total of 150 questionnaires were issued by the researchers. Although 129 questionnaires were received, only 117 of them were valid. The items on the questionnaire were in a multiple-choice format. The highest value for the attitude factor in this study was.708, indicating that there is a strong relationship between attitude and students learning behaviour.

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Murphy, Jack, and Sean Arkins. "Equine learning behaviour." Behavioural Processes 76, no. 1 (September 2007): 1–13. http://dx.doi.org/10.1016/j.beproc.2006.06.009.

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Turčaník, Michal. "Network User Behaviour Analysis by Machine Learning Methods." Information & Security: An International Journal 50 (2021): 66–78. http://dx.doi.org/10.11610/isij.5014.

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Head, George. "Better Learning – Better Behaviour." Scottish Educational Review 37, no. 2 (March 27, 2005): 94–103. http://dx.doi.org/10.1163/27730840-03702002.

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In our efforts to address the problem of pupil behaviour in Scottish schools, perhaps the least effectively supported members of the school community have been teachers. A range of programmes has been used to support pupils, principally through strategies aimed at behaviour modification. Moreover, policy guidelines have also suggested that, in order to minimise disruption to their own and others’ learning, the starting point to dealing with the learning of young people experiencing social, emotional or behavioural difficulties (SEBD) is to deal with their behaviour. In particular, the Report of the Discipline Task Group, Better Learning – Better Behaviour (SEED, 2001) might be seen as prioritising behaviour over learning. This paper argues that behaviour and learning are inextricably linked and that dealing with behaviour as a prerequisite to addressing learning, therefore, may be the wrong starting point, thereby placing unfair expectations on both pupils and teachers. Additionally, if there is such a thing as ‘inappropriate’ behaviour, then the ‘appropriate’ behaviour with which it should be replaced is learning behaviour. A pedagogical focus on learning allows a conceptualisation of SEBD as a learning difficulty, thereby reconsidering the rights of young people who may be experiencing SEBD as co-terminus with, rather than in competition with, the rights of other learners (Visser and Stokes, 2003). Finally, the paper examines one possible pedagogical approach, namely metacognition and a mediational style of teaching, as a way of supporting teachers to deal with SEBD as a learning difficulty.

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Pilling, R. "Learning disability: challenging behaviour." British Journal of Ophthalmology 92, no. 10 (September 24, 2008): 1436. http://dx.doi.org/10.1136/bjo.2008.147140.

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Richardson, Greg. "Child behaviour LEARNING DISABILITY." Early Years Educator 2, no. 4 (August 2000): 46–47. http://dx.doi.org/10.12968/eyed.2000.2.4.15462.

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Winwood, Jo. "Behaviour for Learning: Proactive approaches to behaviour management." Professional Development in Education 37, no. 1 (February 2011): 167–69. http://dx.doi.org/10.1080/19415250903457687.

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van der Sluis, Lidewey. "Learning behaviour and learning opportunities as career stimuli." Journal of Workplace Learning 14, no. 1 (February 2002): 19–29. http://dx.doi.org/10.1108/13665620210422406.

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Kapmeier, Florian. "Common learning and opportunistic behaviour in learning alliances." Systems Research and Behavioral Science 25, no. 4 (September 24, 2008): 549–73. http://dx.doi.org/10.1002/sres.910.

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Mathieson, Kay. "Learning to read children's behaviour." Nursery World 2014, no. 24 (December 2014): 32–33. http://dx.doi.org/10.12968/nuwa.2014.24.32.

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Brown, Claire C., Keith J. Topping, Carlen Henington, and Christopher H. Skinner. "Peer Monitoring of Learning Behaviour." Educational Psychology in Practice 15, no. 3 (October 1999): 174–82. http://dx.doi.org/10.1080/0266736990150304.

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Hughes, R. N., M. J. Kaiser, P. A. Mackney, and K. Warburton. "Optimizing foraging behaviour through learning." Journal of Fish Biology 41, sb (December 1992): 77–91. http://dx.doi.org/10.1111/j.1095-8649.1992.tb03870.x.

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Hentschel, H. G. E., and Z. Jiang. "Learning to control dynamical behaviour." Physica D: Nonlinear Phenomena 67, no. 1-3 (August 1993): 141–50. http://dx.doi.org/10.1016/0167-2789(93)90202-c.

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Dreosti, Elena, and Hernán López-Schier. "Animal Behaviour: Learning Social Distancing." Current Biology 30, no. 20 (October 2020): R1275—R1276. http://dx.doi.org/10.1016/j.cub.2020.08.072.

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McGreevy, P. D., P. K. Della Torre, and D. L. Evans. "Animal Behaviour Learning Environment: Software to Facilitate Learning in Canine and Feline Behaviour Therapy." Journal of Veterinary Medical Education 30, no. 4 (December 2003): 308–17. http://dx.doi.org/10.3138/jvme.30.4.308.

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Hollósi, Gergely, Csaba Lukovszki, Máté Bancsics, and Gábor Magyar. "Traffic Swarm Behaviour: Machine Learning and Game Theory in Behaviour Analysis." Infocommunications journal 13, no. 4 (2021): 19–27. http://dx.doi.org/10.36244/icj.2021.4.3.

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High density traffic on highways and city streets consists of endless interactions among participants. These interactions and the corresponding behaviours have great impact not only on throughput of traffic but also on safety, comfort and economy. Because of this, there is a great interest in deeper understanding of these interactions and concluding the impacts on traffic participants. This paper explores and maps the world of traffic behaviour analysis, especially researches focusing on groups of vehicles called traffic swarm, while presents the state-of-the-art methods and algorithms. The conclusion of this paper states that there are special areas of traffic behaviour analysis which have great research potential in the near future to describe traffic behaviour in more detail than present methods.

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Hertz, Uri. "Learning how to behave: cognitive learning processes account for asymmetries in adaptation to social norms." Proceedings of the Royal Society B: Biological Sciences 288, no. 1952 (June 2, 2021): 20210293. http://dx.doi.org/10.1098/rspb.2021.0293.

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Changes to social settings caused by migration, cultural change or pandemics force us to adapt to new social norms. Social norms provide groups of individuals with behavioural prescriptions and therefore can be inferred by observing their behaviour. This work aims to examine how cognitive learning processes affect adaptation and learning of new social norms. Using a multiplayer game, I found that participants initially complied with various social norms exhibited by the behaviour of bot-players. After gaining experience with one norm, adaptation to a new norm was observed in all cases but one, where an active-harm norm was resistant to adaptation. Using computational learning models, I found that active behaviours were learned faster than omissions, and harmful behaviours were more readily attributed to all group members than beneficial behaviours. These results provide a cognitive foundation for learning and adaptation to descriptive norms and can inform future investigations of group-level learning and cross-cultural adaptation.

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Widmann, Andreas, and Regina H. Mulder. "Team learning behaviours and innovative work behaviour in work teams." European Journal of Innovation Management 21, no. 3 (August 13, 2018): 501–20. http://dx.doi.org/10.1108/ejim-12-2017-0194.

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Purpose The purpose of this paper is to get deeper insight into the complex nature of the relationship between team learning conditions, team learning behaviours (TLBs) and innovative work behaviour (IWB) by considering and combining different neglected aspects in research. Design/methodology/approach A questionnaire was filled out by 593 vocational educators of 117 interdisciplinary work teams in vocational colleges in Germany. Correlations were calculated and structural equation modelling at two levels was conducted. Findings The results indicate that TLBs, especially team reflexivity and boundary spanning, relate positively to IWB. Furthermore, team structure, task interdependence and group potency relate positively to TLBs. It means that TLBs can be fostered by establishing these team learning conditions and, thus, IWB can be fostered. Research limitations/implications The main limitation of the study is that the data collection was cross-sectional. Longitudinal studies are required to capture the dynamic character of team learning and to identify causal relationships. Practical implications It is important to make all employees in vocational education aware of the importance of TLBs especially of team reflexivity and boundary spanning. Originality/value This study provides practical implications for organisations to foster IWB and indications for a better understanding of the relationship between team learning conditions, TLBs and IWB considering and combining different neglected aspects such as examining TLBs separated in one study.

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Et. al., Siti Daleela Mohd Wahid,. "Cyber Security Behaviorin Online Distance Learning: Utilizing National E-Learning Policy." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 5 (April 10, 2021): 1719–28. http://dx.doi.org/10.17762/turcomat.v12i5.2167.

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This present study discovers cybersecurity awareness in online distance learning (ODL) during the pandemic crisis. ODL is an excellent way of teaching and learning during this catastrophe. The Government has imposed the National E-learning Policy to support ODL procedures. Unfortunately, the policies have not been carefully planned on security elements. Therefore, by utilizing Information Security Awareness Capability Model and Situation Awareness-Oriented Cyber Security Education Model, we able to: (1) design the security elements for National e-Learning Policy (2) develop a conceptual model of security behavior that benefits ODL procedure. Principally, four factors are demanding attention in the domain of cybersecurity features. On the other hand, there are partially supported hypotheses between the dimensions of cybersecurity and behaviour. Nutshell, we believe our paper is extending the body of knowledge in cybersecurity elements, awareness, and behaviour literature. Future direction, limitation, and conclusion have been thoroughly discussed.

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Sherwin, C. M., C. M. Heyes, C. Leeb, and C. J. Nicol. "The effect of demonstrator reward on social learning of operant key pecking by domestic hens." Proceedings of the British Society of Animal Science 2001 (2001): OC2. http://dx.doi.org/10.1017/s1752756200006360.

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Social learning is said to occur when social interaction facilitates the acquisition of a novel pattern of behaviour. It usually takes the form of an experienced animal (the demonstrator) performing a behaviour such that a naive animal (the observer) subsequently expresses the same novel behaviour, earlier or more completely than it would have done using individual learning. Social learning is involved in the transmission of a great variety of behaviours, e.g. tool-use, food preferences, and has also been implicated in maladaptive behaviours such as stereotypies in voles. In studies of social learning, the observers usually see the demonstrators receive a reward for performing the required behaviour. But, the role of the reward has rarely been investigated and results have been equivocal. Understanding the role of demonstrator reward on social learning is necessary to assess the cognitive abilities of individuals of different species, and aids understanding of the transmission of maladaptive behaviours.

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Hou, Huaidian, and Lingxiao Wang. "Measuring Dynamics in Evacuation Behaviour with Deep Learning." Entropy 24, no. 2 (January 27, 2022): 198. http://dx.doi.org/10.3390/e24020198.

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Bounded rationality is one crucial component in human behaviours. It plays a key role in the typical collective behaviour of evacuation, in which heterogeneous information can lead to deviations from optimal choices. In this study, we propose a framework of deep learning to extract a key dynamical parameter that drives crowd evacuation behaviour in a cellular automaton (CA) model. On simulation data sets of a replica dynamic CA model, trained deep convolution neural networks (CNNs) can accurately predict dynamics from multiple frames of images. The dynamical parameter could be regarded as a factor describing the optimality of path-choosing decisions in evacuation behaviour. In addition, it should be noted that the performance of this method is robust to incomplete images, in which the information loss caused by cutting images does not hinder the feasibility of the method. Moreover, this framework provides us with a platform to quantitatively measure the optimal strategy in evacuation, and this approach can be extended to other well-designed crowd behaviour experiments.

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Collacott, Richard A., Sally-Ann Cooper, David Branford, and Catherine McGrother. "Epidemiology of self-injurious behaviour in adults with learning disabilities." British Journal of Psychiatry 173, no. 5 (November 1998): 428–32. http://dx.doi.org/10.1192/bjp.173.5.428.

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BackgroundThere have been few epidemiological studies of the disabling and poorly understood disorder self-injurious behaviour among adults with learning disabilities.MethodInterviews were undertaken with the carers of adults known to the Leicestershire Learning Disabilities Register (n=2277). The Disability Assessment Schedule was used and information was also collected on demographic characteristics, developmental and physical status.ResultsSelf-injurious behaviour was present in 17.4% of the population. In 1.7% self-injurious behaviour occurred frequently and was severe. There was no gender difference between those with and without self-injurious behaviour. Both the chronological age and developmental quotient of individuals with self-injurious behaviour were lower than those of individuals without self-injurious behaviour. Autistic symptoms were more common among those with self-injurious behaviour. The association of self-injurious behaviour with a wide range of other maladaptive behaviours was highly significant. Logistic regression analysis retained age, developmental quotient, hearing status, immobility and number of autistic symptoms as explanatory variables for self-injurious behaviour.ConclusionsSelf-injurious behaviour is a prevalent and disabling disorder among adults with learning disabilities.

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Chua, Sook-Ling, Stephen Marsland, and Hans Guesgen. "Unsupervised Learning of Human Behaviours." Proceedings of the AAAI Conference on Artificial Intelligence 25, no. 1 (August 4, 2011): 319–24. http://dx.doi.org/10.1609/aaai.v25i1.7911.

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Behaviour recognition is the process of inferring the behaviour of an individual from a series of observations acquired from sensors such as in a smart home. The majority of existing behaviour recognition systems are based on supervised learning algorithms, which means that training them requires a preprocessed, annotated dataset. Unfortunately, annotating a dataset is a rather tedious process and one that is prone to error. In this paper we suggest a way to identify structure in the data based on text compression and the edit distance between words, without any prior labelling. We demonstrate that by using this method we can automatically identify patterns and segment the data into patterns that correspond to human behaviours. To evaluate the effectiveness of our proposed method, we use a dataset from a smart home and compare the labels produced by our approach with the labels assigned by a human to the activities in the dataset. We find that the results are promising and show significant improvement in the recognition accuracy over Self-Organising Maps (SOMs).

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Zemančíková, Vladimíra, and Ivana Mikulová. "Problem Behaviour of Pupils with Specific Learning Disabilities in Teachers’ Reflections." New Educational Review 70, no. 4 (2022): 145–55. http://dx.doi.org/10.15804/tner.2022.70.4.12.

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The research aimed to find out the manifestations and rate of occurrence of problem behaviour among pupils with specific developmental learning disabilities in teachers’ reflections. Differences in the rate of occurrence of pupils’ problem behaviour were compared with regard to their current level of education, position in the class, and academic achievement. Data were gathered by content analysis of text documents – pupil pedagogical profiles including the Conners Rating Scale for teachers (1969, 1999). Data were processed by SPSS, the method of statistical inference, Mann-Whitney U-test, and Kruskal-Wallis analysis of variance. A variability of SLD pupils’ behaviours was discovered. The most pronounced manifestations included internalising problem behaviours; externalising problem behaviours were mostly disruptive and inattentive behaviours. SLD pupils with poor academic achievement were characterised by significantly more frequent manifestations of problem behaviour.

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Wang, Yi, and Yong Ling Jiang. "Research on Learning Behavior Based on ARCS Learning Motivation Model." Advances in Science and Technology 105 (April 2021): 356–63. http://dx.doi.org/10.4028/www.scientific.net/ast.105.356.

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Based on the ARCS Motivation Model proposed by John M. Keller, the instructional design of blended learning is carried out, and the "Python Programming" course is taken as an example for empirical research. Pearson correlation analysis and Apriori algorithm are used to analyse the data of students' learning behavior. The results show that the pre-class preview learning behaviour has a significant impact on students' learning process. Through the association analysis of learning process, it is found that the difference between pre-class preview and self-test learning behavior has a significant impact on the learning outcomes. The empirical conclusion of this paper has important reference value for optimizing blended learning methods and data mining analysis based on learning behavior, so as to support teachers to carry out personalized guidance and feedback for students.

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Bhaumik, Sabyasachi, David Branford, Catherine McGrother, and Catherine Thorp. "Autistic traits in adults with learning disabilities." British Journal of Psychiatry 170, no. 6 (June 1997): 502–6. http://dx.doi.org/10.1192/bjp.170.6.502.

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BackgroundAlthough many adults with learning disabilities show features of autistic syndrome, there have been very few population-based studies. We explored the prevalence of autistic traits and their association with maladaptive behaviours in a geographically defined population of adults with learning disabilities.MethodThe carers of 220l adults with learning disabilities were interviewed, and information was sought concerning aspects of their behaviour and ability. Individuals were scored according to the number of core autistic traits displayed. The prevalence of autistic traits was examined in respect of aspects of behaviour and ability.ResultsAutistic traits were common among adults with learning disabilities. Those with a higher number of autistic traits were more likely to be profoundly learning disabled and demonstrate awide range of challenging behaviours.ConclusionsMany adults with learning disabilities demonstrate autistic traits. The relationship of autistic traits with challenging behaviour has major implications in service planning and delivery.

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Mataric, Maja J. "Behaviour-based control: examples from navigation, learning, and group behaviour." Journal of Experimental & Theoretical Artificial Intelligence 9, no. 2-3 (April 1997): 323–36. http://dx.doi.org/10.1080/095281397147149.

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Enquist, Magnus, Johan Lind, and Stefano Ghirlanda. "The power of associative learning and the ontogeny of optimal behaviour." Royal Society Open Science 3, no. 11 (November 2016): 160734. http://dx.doi.org/10.1098/rsos.160734.

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Behaving efficiently (optimally or near-optimally) is central to animals' adaptation to their environment. Much evolutionary biology assumes, implicitly or explicitly, that optimal behavioural strategies are genetically inherited, yet the behaviour of many animals depends crucially on learning. The question of how learning contributes to optimal behaviour is largely open. Here we propose an associative learning model that can learn optimal behaviour in a wide variety of ecologically relevant circumstances. The model learns through chaining, a term introduced by Skinner to indicate learning of behaviour sequences by linking together shorter sequences or single behaviours. Our model formalizes the concept of conditioned reinforcement (the learning process that underlies chaining) and is closely related to optimization algorithms from machine learning. Our analysis dispels the common belief that associative learning is too limited to produce ‘intelligent’ behaviour such as tool use, social learning, self-control or expectations of the future. Furthermore, the model readily accounts for both instinctual and learned aspects of behaviour, clarifying how genetic evolution and individual learning complement each other, and bridging a long-standing divide between ethology and psychology. We conclude that associative learning, supported by genetic predispositions and including the oft-neglected phenomenon of conditioned reinforcement, may suffice to explain the ontogeny of optimal behaviour in most, if not all, non-human animals. Our results establish associative learning as a more powerful optimizing mechanism than acknowledged by current opinion.

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Khaola, Peter. "Organisational citizenship behaviour within learning environments." International Journal of Management Education 7, no. 1 (October 29, 2008): 73–80. http://dx.doi.org/10.3794/ijme.71.219.

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Lim, Kok Khiang, and Chei Sian Lee. "Nudging Learning Behaviour: A Systematic Review." Proceedings of the Association for Information Science and Technology 59, no. 1 (October 2022): 744–46. http://dx.doi.org/10.1002/pra2.712.

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Nadhirin, N. "Values Based Superior Students’ Learning Behaviour." ADDIN 12, no. 1 (January 9, 2019): 133. http://dx.doi.org/10.21043/addin.v1i1.3592.

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The purpose of this research is to find (1) organizational behavior in superior school students learn (2) the source of values that underlies the attitude and behavior of superior student learning (3) superior student learning behavior in school and (4) learning interaction between teacher and student excel at school. This research uses qualitative approach and pospositivistic paradigm. The research data was collected by interview, observation and documentation. Technique of validity test data use triangulation, cover angulasi technique, source and time. Data were analyzed by Miles Hubermans interactive cycling technique, with cycle collecting, reducting, displaying and verifying. The subjects of this research are the leaders of madrasah, faculty, students and stakelholders of madrasah. Research location at MA. NU Banat, Kudus, Central Java, Indonesia. The results of this study are (1) Students who have good pretation in the field of academic and non academic are students who study in school organization unit that has commitment and spirit to go forward. A good and conducive organizational culture that is maintained by all members of the organization is very supportive to the achievement of superior and competitive student achievement (2) The source of values or outlooks that make the students become outstanding achievers is the accumulation of values formed from the religious family environment and dicipline, school environment consistent with the practice of religion in the school environment that inculcates values of virtue, dicipline in learning, honest, competitive and heed the norms prevailing in society. (3) behavioral typology and high school student learning attitudes are responsive stimuli. The more rules and structured tasks created by the school and the subject teachers, the students' attitudes and motivation will be more intense and vice versa (4) outstanding achievement students have a close relationship with the teacher. Teachers for students who excel are teachers who are not only as parents, as mentors, as well as teachers who can put themselves as friends of students, who can be invited to communicate closely and there is openness in various problems and teachers help students to solve problems encountered so that good achievement is greatly assisted by his teachers who are concerned primarily on non-academic issues.

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Rivers, Sue. "The learning journey 3: Changing behaviour." Practice Nursing 18, no. 4 (April 2007): 190–93. http://dx.doi.org/10.12968/pnur.2007.18.4.23298.

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Scarpa, C. "DYNAMIC MONOPOLIST'S BEHAVIOUR AND CONSUMER LEARNING*." Metroeconomica 41, no. 1 (February 1990): 51–72. http://dx.doi.org/10.1111/j.1467-999x.1990.tb00457.x.

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Touzet, Claude F. "Neural reinforcement learning for behaviour synthesis." Robotics and Autonomous Systems 22, no. 3-4 (December 1997): 251–81. http://dx.doi.org/10.1016/s0921-8890(97)00042-0.

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Zizzo, Daniel John. "Implicit learning of (boundedly) rational behaviour." Behavioral and Brain Sciences 23, no. 5 (October 2000): 700–701. http://dx.doi.org/10.1017/s0140525x00613432.

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Stanovich & West's target article undervalues the power of implicit learning (particularly reinforcement learning). Implicit learning may allow the learning of more rational responses–and sometimes even generalisation of knowledge–in contexts where explicit, abstract knowledge proves only of limited value, such as for economic decision-making. Four other comments are made.

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Evermann, Joerg, Jana-Rebecca Rehse, and Peter Fettke. "Predicting process behaviour using deep learning." Decision Support Systems 100 (August 2017): 129–40. http://dx.doi.org/10.1016/j.dss.2017.04.003.

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Boakes, R. A. "Book Review: Adaptive Behaviour and Learning." Quarterly Journal of Experimental Psychology Section B 37, no. 3b (August 1985): 275–76. http://dx.doi.org/10.1080/14640748508402100.

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Colucci, Domenico, and Vincenzo Valori. "Error learning behaviour and stability revisited." Journal of Economic Dynamics and Control 29, no. 3 (March 2005): 371–88. http://dx.doi.org/10.1016/j.jedc.2004.01.002.

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Scholz-Reiter, B., and T. Hamann. "The behaviour of learning production control." CIRP Annals 57, no. 1 (2008): 459–62. http://dx.doi.org/10.1016/j.cirp.2008.03.104.

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Collett, Thomas S. "Insect Behaviour: Learning for the Future." Current Biology 18, no. 3 (February 2008): R131—R134. http://dx.doi.org/10.1016/j.cub.2007.11.052.

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Cloutier, Sylvie, Ruth C. Newberry, Kristen Honda, and J. Richard Alldredge. "Cannibalistic behaviour spread by social learning." Animal Behaviour 63, no. 6 (June 2002): 1153–62. http://dx.doi.org/10.1006/anbe.2002.3017.

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Hunt, Gavin R., and Russell D. Gray. "Genetic assimilation of behaviour does not eliminate learning and innovation." Behavioral and Brain Sciences 30, no. 4 (August 2007): 412–13. http://dx.doi.org/10.1017/s0140525x07002439.

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AbstractRamsey et al. attempt to clarify methodological issues for identifying innovative behaviour. Their effort is seriously weakened by an underlying presumption that the behavior of primates is generally learned and that of non-primates is generally “innate.” This presumption is based on a poor grasp of the non-primate literature and a flawed understanding of how learned behaviour is genetically assimilated.

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Rahmawati, Rizqi, Saiful Ridlo, and Sri Sukaesih. "Analysis of the Effectiveness of Learning Models against Students’ Innovative Behaviour." Journal of Biology Education 7, no. 2 (September 7, 2018): 127–36. http://dx.doi.org/10.15294/jbe.v7i2.24266.

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Practicum become an appropriate method to give provisions in empirical experience especially for college student of Biology Education. Practicum was believed could show university students’ innovative behavior. The concrete form from using practicum method is learning model application that include learning syntax from the beginning to the end. Therefore, a research was did to analyze relation between practicum method towards innovative behaviour and the effectivity of it. Based on the result of regression analysis, all models give significance value p < 0.05 so could be known that every learning model give significance influence toward the formation of university students’ innovative behavior. Based on correlation coefficient analysis could be known that PJBL learning model give contribution value of 86.2% followed by guided inquiry of 85.4%, experiment model of 76.3% and observation model with contribution value of 64.7% toward the formation of university students’ innovative behavior. Based on the results of variance similarity analysis could be known that PJBL model is the most effictive model to form innovative behavior with difference value of 17.80 compared with other learning models. The result of research showing that all of the learning models when used on practicum relating the formation of innovative behaviour. Project based learning model gave contribution most effective towards innovative behaviour of the college students in Biology Education study program.

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Alghamdi, Rashed. "EFL Learners’ Behaviour States During Cooperative Learning Strategy." International Journal of Linguistics 10, no. 6 (December 6, 2018): 64. http://dx.doi.org/10.5296/ijl.v10i6.14006.

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To examine the impact of cooperative learning strategy on the behaviour states of EFL learners, a 3-month study was conducted in 4 government secondary schools in EFL context (Saudi Arabia). This study aims to identify the effect of cooperative learning in comparison to traditional learning in learning English grammar on the behaviour states of EFL Learners. This study contributed to the knowledge about how EFL learners behave when they interact cooperatively together in cooperative learning groups in comparison to their colleagues who learn in traditional learning. In this study, the participants were 139 tenth grade male students, in 4 male government secondary schools in Al-Baha city, in Saudi Arabia context.An examination of the Kruskal‑Wallis tests shows that the EFL learners in the experimental conditions displayed more cooperative behavioural states and less non‑cooperative states, individual task‑oriented, and individual non‑task behaviours than their classmates in the control condition. In addition, outcome scores were, on average, higher in the experimental condition for cooperative behavioural outcomes. They were lower in the experimental condition for non‑cooperation behaviour, individual task oriented and individual non‑task oriented.

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Edmonstone, John. "Learning and development in action learning: the energy investment model." Industrial and Commercial Training 35, no. 1 (February 1, 2003): 26–28. http://dx.doi.org/10.1108/00197850310458216.

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In action learning sets participants bring their personal energy and attitudes. These produce identifiable behaviour styles (not types of people). In the energy investment model four behaviour styles of set members are identified, showing participants’ typical feelings and reactions, the support needed and what helpful questions may be.

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McDonnell, Andrew, Simon Reeves, Amanda Johnson, and Alan Lane. "MANAGING CHALLENGING BEHAVIOUR IN AN ADULT WITH LEARNING DISABILITIES: THE USE OF LOW AROUSAL APPROACH." Behavioural and Cognitive Psychotherapy 26, no. 2 (April 1998): 163–71. http://dx.doi.org/10.1017/s1352465898000174.

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Behaviour change is often a desired outcome for carers and professionals who work with people with learning disabilities and challenging behaviours. Managing these behaviours in the short term is an important step towards this goal. This single case study presents the use of a low arousal approach in managing challenging behaviours in a young man labelled with severe challenging behaviour. This strategy focuses on the interaction of the carers with the client and how their approach has an important impact on the behaviour of the client. The study documents the incidents of challenging behaviour and shows a decline in their frequency from baseline over a one-year period. These gains were maintained at five-month follow-up. The implications for services of these findings are discussed.

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Grohnert, Therese, Roger H. G. Meuwissen, and Wim H. Gijselaers. "Valuing errors for learning: espouse or enact?" Journal of Workplace Learning 29, no. 5 (July 10, 2017): 394–408. http://dx.doi.org/10.1108/jwl-11-2016-0102.

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Purpose This study aims to investigate how organisations can discourage covering up and instead encourage learning from errors through a supportive learning from error climate. In explaining professionals’ learning from error behaviour, this study distinguishes between espoused (verbally expressed) and enacted (behaviourally expressed) values with respect to learning from errors. Design/methodology/approach As part of mandatory training sessions, 150 early-career auditors completed an online questionnaire measuring error orientation and help-seeking behavior after making an error as attitude- and behavior-based measures, next to measuring perceived organizational learning from error climate. Multiple mediation analysis is used to explore direct and indirect effects. Findings Covering up errors was negatively and learning from errors positively related to an organisation’s learning from error climate. For covering up, this relationship is an indirect one – espoused and enacted values need to match. For learning from errors, this relationship is direct: espoused values positively relate to learning behaviour after errors. Practical implications By designing a supportive learning from error climate in which members at all hierarchical levels role-model learning from errors behaviour, organisations can actively discourage covering up and encourage learning from errors. Originality/value This study applies the theory of espoused versus enacted values to learning from error using a triangulation of measures in an understudied research setting: auditing.

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Coulson-Thomas, Colin. "Learning and behaviour: addressing the culture change conundrum: part two." Industrial and Commercial Training 47, no. 4 (June 1, 2015): 182–89. http://dx.doi.org/10.1108/ict-01-2015-0004.

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Purpose – Calls for culture change often result from a desire to change certain behaviours. The purpose of this paper is to summarise some key findings of a five year investigation into quicker and more affordable routes to creating high-performance organisations. It suggests a practical and cost-effective way of quickly changing the behaviour of key work-groups independently of corporate culture which integrates working and learning and simultaneously achieves multiple corporate objectives. Design/methodology/approach – A programme of critical success factor, “issue” and other surveys was complemented with a five-year evaluation of more recent case studies to understand early adoptions of performance support and to assess their results and implications. The applications examined were discussed with the relevant technical architect and the results obtained corroborated with commissioner/user performance data and/or documented assessments/reactions. Findings – The use of performance support which can integrate learning and working represents an affordable way of changing the behaviour of particular and front-line work-groups independently of corporate culture. Changing a culture defined in terms of deeply held attitudes, values and beliefs is problematic, but required changes of behaviour can often be quickly accomplished using performance support, which can also address particular problems and deliver benefits for multiple stakeholders. Practical implications – Many general corporate culture change programmes, HR policies and associated training may be unnecessary and counter-productive if the aim is to quickly change specific behaviours in particular areas. They might also be problematic in organisations that need to embrace a diversity of cultures and encourage a variety of approaches and behaviours across different functions and business units. Performance support which integrates learning and working can be a cost-effective way of changing behaviour, ensuring compliance, enabling people to innovate and remain current and competitive, and delivering multiple objectives without requiring a change of culture or structure. Originality/value – Summarises the main findings of an investigation that has identified deficiencies of contemporary responses to a requirement to change certain behaviours that involve seeking to change a corporate culture and questions their practicality, desirability, time-scale and affordability. It presents an evidence-based alternative approach that is more affordable and can more quickly deliver changes of behaviour required and ensure compliance with relevant laws, regulations, policies and codes.

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Gayatri, Mantri, P. Satheesh, and R. Rajeswara Rao. "Deep Learning for User Behaviour Prediction Using Streaming Analytics." International Journal on Recent and Innovation Trends in Computing and Communication 10, no. 2s (December 31, 2022): 289–97. http://dx.doi.org/10.17762/ijritcc.v10i2s.5946.

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Streams of web user interactions reflect behaviour of customers or users of a web application through which a company is being operated online. The interactions may be in the form of visits to web components and even purchases made by users in case of e-Commerce applications. Modelling user behaviour can help the organizations to ascertain patterns of user behaviours and improve their products and services to meet their needs besides making promotional schemes. There are many existing methods for modelling user behaviour. However, of late, deep learning models are found to be more accurate and useful. In this paper a deep learning based framework is proposed for predicting web user behaviour from streams of user interactions. The framework is based on the mechanisms that exploit Recurrent Neural Network (RNN), one of the deep learning approaches, to learn from low-level features of sequential and streaming data. The mechanisms are used to model user interactions and predict the user behaviour with respect to purchasing items in future. In presence of plenty of items, item embeddings is explored for better results. In addition to this, attention mechanisms are employed to achieve RNN model interoperability. The empirical study revealed that the proposed framework is useful besides helping to evaluate different variants of attention mechanisms and item embeddings.

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Raes, Elisabeth, Anne Boon, Eva Kyndt, and Filip Dochy. "Measuring team learning behaviours through observing verbal team interaction." Journal of Workplace Learning 27, no. 7 (September 14, 2015): 476–500. http://dx.doi.org/10.1108/jwl-01-2015-0006.

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Purpose – This study aims to explore, as an answer to the observed lack of knowledge about actual team learning behaviours, the characteristics of the actual observed basic team learning behaviours and facilitating team learning behaviours more in-depth of three project teams. Over time, team learning in an organisational context has been investigated more and more. In these studies, there is a dominant focus on team members’ perception of team learning behaviours. Design/methodology/approach – A coding schema is created to observe actual team learning behaviours in interaction between team members in two steps: verbal contributions by individual team members are coded to identify the type of sharing behaviour and, when applicable, these individual verbal behaviours are build up to basic and facilitating team learning behaviours. Based on these observations, an analysis of team learning behaviours is conducted to identify the specific characteristics of these behaviours. Findings – An important conclusion of this study is the lack of clarity about the line of demarcation between individual contributions and learning behaviours and team learning behaviours. Additionally, it is clear that the conceptualisations of team learning behaviour in previous research neglect to a large extend the nuances and depth of team learning behaviours. Originality/value – Due to the innovative approach to study team learning behaviours, this study is of great value to the research field of teamwork for two reasons: the creation of a coding schema to analyse team learning behaviours and the findings that resulted from this approach.

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