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Journal articles on the topic 'Factors affecting learning'

Author: Grafiati

Published: 4 June 2021

Last updated: 13 February 2022

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1

Peters, Linda D., Andrew D. Pressey, and Wesley J. Johnston. "Contingent factors affecting network learning." Journal of Business Research 69, no. 7 (July 2016): 2507–15. http://dx.doi.org/10.1016/j.jbusres.2016.02.020.

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Ariadni, Dwi Karina, Siti Zahara Nasution, and Reni Asmara Ariga. "Factors Affecting Nursing Students’ Learning." Caring: Indonesian Journal of Nursing Science 2, no. 1 (July 21, 2020): 49–55. http://dx.doi.org/10.32734/ijns.v2i1.4167.

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High learning motivation is influenced by some factors from intrinsic factor (in self) and extrinsic factor. This study aims to describe the intrinsic factors and extrinsic factors in learning motivation. This is a descriptive design study with quota random sampling. 90 respondents were involved in this study. Results of intrinsic factors measured by interest in the field of knowledge studied: 47.8% of respondents collect tasks given in accordance with the time set, and 41.1% of respondents diligently follow the lecture. The results of the study of extrinsic factors are measured by the quality of lecturers who teach: 51.1% of lecturers often provide questions clearly and briefly. Based on the method of lecturing: simulation methods in the laboratory often increase the motivation to learn. Based on the lecture’s room: 57.8% stated that a clean lecture’s room can improve the concentration of learning. Based on the complete book in the library: 47.8% encourage respondents to do the task quickly. Based on the learning facilities: 47.8% are always motivated to learn if the lecturer uses LCD. Support of parents (76.7%) in meeting the needs of respondents in learning.The management of nursing education is suggested to motivate students during lectures based on intrinsic factors and extrinsic factors. Keywords : learning motivation, affecting factor, nursing student

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Wang, Fei, Bokuan Zhang, and Ruishu Gong. "Factors Affecting Road Rating." Frontiers Research of Architecture and Engineering 3, no. 1 (March 30, 2020): 17. http://dx.doi.org/10.30564/frae.v3i1.1658.

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The decision of traffic congestion degree is an important research topic today. In severe traffic jams, the speed of the car is slow, and the speed estimate is very inaccurate.This paper first uses the data collected by Google Maps to reclassify road levels by using analytic hierarchy process. The vehicle speed, road length, normal travel time, traffic volume, and road level are selected as the input features of the limit learning machine, and the delay coefficient is selected. As the limit learning machine as the output value, 10-fold cross-validation is used. Compared with the traditional neural network, it is found that the training speed of the limit learning machine is 10 times that of the traditional neural network, and the mean square error is 0.8 times that of the traditional neural network. The stability of the model Significantly higher than traditional neural networks.Finally, the delay coefficient predicted by the extreme learning machine and the normal travel time are combined with the knowledge of queuing theory to finally predict the delay time.

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Rahman, Hamidah Abdul, Azizah Rajab, Shah Rollah Abdul Wahab, Faizah Mohd Nor, Wan Zarina Wan Zakaria, and Mohd Asyraf Badli. "Factors Affecting Motivation in Language Learning." International Journal of Information and Education Technology 7, no. 7 (2017): 543–47. http://dx.doi.org/10.18178/ijiet.2017.7.7.927.

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Lee, Jeongmin, Jiyae Noh, and Younhwa Chung. "Investigating Factors Affecting Flipped Learning Outcomes." Journal of The Korean Association of Information Education 20, no. 1 (March 31, 2016): 57–68. http://dx.doi.org/10.14352/jkaie.2016.20.1.57.

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Tangamchit, Poj, John M. Dolan, and Pradeep K. Khosla. "Crucial Factors Affecting Cooperative Multirobot Learning." Intelligent Automation & Soft Computing 10, no. 4 (January 2004): 323–35. http://dx.doi.org/10.1080/10798587.2004.10642886.

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7

Glass, J. Conrad. "FACTORS AFFECTING LEARNING IN OLDER ADULTS." Educational Gerontology 22, no. 4 (January 1996): 359–72. http://dx.doi.org/10.1080/0360127960220405.

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Willy A. Renandya. "Essential Factors Affecting EFL Learning Outcomes." English Teaching 68, no. 4 (December 2013): 23–41. http://dx.doi.org/10.15858/engtea.68.4.201312.23.

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Pratama, Yoga, Rudy Hartanto, and Sri Suning Kusumawardani. "Validating YouTube Factors Affecting Learning Performance." IOP Conference Series: Materials Science and Engineering 325 (March 2018): 012003. http://dx.doi.org/10.1088/1757-899x/325/1/012003.

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Andreou, G., F. Vlachos, and E. Andreou. "Affecting Factors in Second Language Learning." Journal of Psycholinguistic Research 34, no. 5 (September 2005): 429–38. http://dx.doi.org/10.1007/s10936-005-6202-0.

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11

Jović, Marija, Milica Kostic Stankovic, and Ema Neskovic. "Factors Affecting Students’ Attitudes towards E-Learning." Management:Journal of Sustainable Business and Management Solutions in Emerging Economies 22, no. 2 (September 21, 2017): 73. http://dx.doi.org/10.7595/10.7595/management.fon.2017.0016.

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E-learning is becoming a widespread method of gaining knowledge in a global environment. Accessibility and variety of online content encourage more people to get involved in learning from digital resources. However, there has been limited research exploring the factors that could influence students’ attitudes regarding e-learning. In this study, field research was conducted to determine which factors affect students’ attitudes towards e-learning. The questionnaire was developed to collect data about factors that influence attitudes towards e-learning. A total of 286 students were the study cohort. Three factors were identified using principal component analysis: e-learning usefulness, ease of use, and content design. Regression analysis was conducted to determine the strength of the factors influencing attitudes towards e-learning. All factors had a significant influence on attitude towards e-learning. Usefulness of e-learning had the strongest impact on students’ e-learning intention. Our study will contribute to the existing work in this field by emphasizing the importance of perception of content design on attitudes towards e-learning.

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Jovi�, Marija, Milica Kostic Stankovic, and Ema Neskovic. "Factors Affecting Students� Attitudes towards E-Learning." Management:Journal of Sustainable Business and Management Solutions in Emerging Economies 22, no. 2 (September 21, 2017): 73. http://dx.doi.org/10.7595/management.fon.2017.0016.

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E-learning is becoming a widespread method of gaining knowledge in a global environment. Accessibility and variety of online content encourage more people to get involved in learning from digital resources. However, there has been limited research exploring the factors that could influence students� attitudes regarding e-learning. In this study, field research was conducted to determine which factors affect students� attitudes towards e-learning. The questionnaire was developed to collect data about factors that influence attitudes towards e-learning. A total of 286 students were the study cohort. Three factors were identified using principal component analysis: e-learning usefulness, ease of use, and content design. Regression analysis was conducted to determine the strength of the factors influencing attitudes towards e-learning. All factors had a significant influence on attitude towards e-learning. Usefulness of e-learning had the strongest impact on students� e-learning intention. Our study will contribute to the existing work in this field by emphasizing the importance of perception of content design on attitudes towards e-learning.

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13

Dewi, N. N., and R. Wibowo. "FACTORS AFFECTING THE LEARNING SPIRIT OF STUDENTS." Russian Journal of Agricultural and Socio-Economic Sciences 3, no. 99 (March 12, 2020): 12–28. http://dx.doi.org/10.18551/rjoas.2020-03.03.

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14

Thomas, David R., Todd Stengel, Leslie Sherman, and Margaret Woodford. "FACTORS AFFECTING CONDITIONAL DISCRIMINATION LEARNING BY PIGEONS." Journal of the Experimental Analysis of Behavior 48, no. 2 (September 1987): 277–87. http://dx.doi.org/10.1901/jeab.1987.48-277.

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15

Rahman, Roselainy Abdul, John H. Mason, and Yudariah Mohamad Yusof. "Factors Affecting Students’ Change of Learning Behaviour." Procedia - Social and Behavioral Sciences 56 (October 2012): 213–22. http://dx.doi.org/10.1016/j.sbspro.2012.09.648.

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Xiong, Chang, Qianwen Xu, Meiy Liu, and Victor Chang. "Factors affecting student satisfaction in e-learning." International Journal of Business and Systems Research 1, no. 1 (2022): 1. http://dx.doi.org/10.1504/ijbsr.2022.10031981.

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Kyung Ja Kim. "Language Learning Belief Factors Affecting English Achievement." English Teaching 67, no. 4 (December 2012): 173–94. http://dx.doi.org/10.15858/engtea.67.4.201212.173.

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18

Lim, Hyochang, Sang-Gun Lee, and Kichan Nam. "Validating E-learning factors affecting training effectiveness." International Journal of Information Management 27, no. 1 (February 2007): 22–35. http://dx.doi.org/10.1016/j.ijinfomgt.2006.08.002.

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19

McDonald, Deborah Dillon, Marjorie Wiczorek, and Cheryl Walker. "Factors Affecting Learning During Health Education Sessions." Clinical Nursing Research 13, no. 2 (May 2004): 156–67. http://dx.doi.org/10.1177/1054773803261113.

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Muda @ Yusof, Nazuha, Zokree Abdul Karim, Ruzaidah A. Rashid, and Zamzulani Mohamed. "Factors Affecting Students’ Achievement in Mathematics." Jurnal Intelek 14, no. 2 (November 29, 2019): 198–207. http://dx.doi.org/10.24191/ji.v14i2.235.

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Most programs at the university level require completion of mathematics courses. To survive inuniversity, those who are taking mathematics courses should succeed in their examination so that this canbe a path for them to proceed smoothly in their study. This research investigates the factors contributingtowards achievement in mathematics at a public university. The identified factors are students’ attitude,student-centered learning and classroom environments. The data was collected randomly from 86students who took business mathematics course in 2018 through a distribution of questionnaires. Thisstudy focused on the measurement model and structural model of Partial Least Square analysis. Thefindings indicate that students’ attitude most significantly affected the achievement in mathematics,followed by students’ centered learning. Meanwhile, classroom environment is found as an insignificantfactor of the achievement in mathematics. As a conclusion, students’ attitude is the most influential factorin mathematics achievement compared to students’ centered learning and classroom environments.Therefore, the management of higher education should focus on the empowerment of students’ attitudetowards mathematics subject and improve the quality of student-centered learning at the university. Keywords: achievement in mathematics, students’ attitude, student-centered learning, classroom environments, Partial Least Square

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21

Lam, Pamela, and Sarbari Bordia. "Factors Affecting Student Choice of e-Learning over Traditional Learning." International Journal of Learning: Annual Review 14, no. 12 (2008): 131–40. http://dx.doi.org/10.18848/1447-9494/cgp/v14i12/45546.

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Thomas, Lauren Josie, Michael Parsons, and Dean Whitcombe. "Assessment in Smart Learning Environments: Psychological factors affecting perceived learning." Computers in Human Behavior 95 (June 2019): 197–207. http://dx.doi.org/10.1016/j.chb.2018.11.037.

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23

Lee, Jeongmin, and Seungeun Oh. "Learning Presence Factors Affecting Learning Outcomes in Facebook-based Collaborative Learning Environments." Journal of the Korean Association of Information Education 17, no. 3 (September 30, 2013): 305–16. http://dx.doi.org/10.14352/jkaie.2013.17.3.305.

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24

Senaratne, Sanduni I., and Samantha M. Samarasinghe. "Factors Affecting the Intention to Adopt M-Learning." International Business Research 12, no. 2 (January 21, 2019): 150. http://dx.doi.org/10.5539/ibr.v12n2p150.

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Over the recent years, emerging technological applications have been used for making student learning more effective and interactive. M-Learning has been one such technological initiative which has shown promising benefits in the higher education context. Even though the importance of mobile learning has been researched by many, the factors influencing mobile learning adoption intention has not been addressed sufficiently, particularly in the Sri Lankan context. Hence, the purpose of this paper was to present a conceptual model to examine the factors influencing the intention to adopt mobile learning by the students engaged in higher education. Based on a comprehensive literature review, this study extended the Technology Acceptance Model (TAM) (Davis, 1989) with mobile self-efficacy, intrinsic motivation to use mobile devices and the system quality of the m-Learning system. The model describes how the aforementioned factors influence the higher education students’ intention to adopt m-Learning via survey data collected from 151 postgraduate students. The findings suggest that the model explained the factors influencing the intention to adopt m-Learning among students in higher education. In detail, the mobile self -efficacy, system quality and intrinsic motivation significantly influenced the intention to adopt m-Learning. The results could be utilized for increasing the adoption of m-Learning practices and developing mobile applications useful for teaching and learning purposes. This study has incorporated three independent constructs in extending the TAM model; namely, system quality, mobile self-efficacy and intrinsic motivation. These were derived from the IS Success theory, Self-efficacy theory and Self-determination theory respectively. Accordingly, this study intends to address the theoretical gap in the higher education context pertaining to the adoption of mobile learning. Since Mobile Self-Efficacy and System Quality were the most significant factors that affect the perceived ease of use and perceived usefulness, these factors should be given prominence when developing mobile enabled Learning Management Systems within institutions.

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유명제 and Ji-Yeon Lee. "Factors Affecting Chinese College Students’ e-Learning Acceptance." Journal of Education & Culture 23, no. 2 (April 2017): 239–58. http://dx.doi.org/10.24159/joec.2017.23.2.239.

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26

Kim, Youngsu. "Exploring Factors Affecting Online Self-Regulated English Learning." Journal of Linguistics Science 88 (March 31, 2019): 25–47. http://dx.doi.org/10.21296/jls.2019.3.88.25.

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27

Ashby, Rachel, and Christine Broughan. "Factors Affecting Students' Usage of Virtual Learning Environments." Psychology Learning & Teaching 2, no. 2 (June 2002): 140–41. http://dx.doi.org/10.2304/plat.2002.2.2.140.

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This report considers the factors that affect students' usage of virtual learning environments (VLE). In particular it explores students' reluctance to engage in the interactive components of the VLE that are essential elements to the learning process. A study at Coventry University found that many students felt embarrassed to use the on-line facilities. In order for students to use the VLE to its fullest potential, it is suggested that students should not simply be expected to embrace this new form of learning without suitable support and guidance from tutors.

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Saleh, Nada, Edmond Prakash, and Rob Manton. "Factors Affecting the Acceptance of Game-based Learning." International Journal of Computer Applications 92, no. 13 (April 18, 2014): 1–10. http://dx.doi.org/10.5120/16066-5201.

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29

Lai, Yung-Yu, and AnAn Chiu. "Factors Affecting Learning Performance of Accounting Information System." Asian Journal of Finance & Accounting 10, no. 1 (May 22, 2018): 257. http://dx.doi.org/10.5296/ajfa.v10i1.13039.

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Due to the advancement of computer and information technology (IT), integrating the information and computing technology into the Accounting curriculum is one of the critical issues. This paper discusses whether the learning attitude towards information technology and the major in which these students enrolled will affect their respective learning performance based on testing results obtained from the questionnaire of the Accounting Information System Contest. Important findings include the following items: 1) Different learning attitude may affect the learning performance; 2) There is a significant difference in terms of the subjects of academic content and associated skills in the Contest for the participated candidates enrolled in different majors. From the results, it is notable that academic institutions should train instructors to help students develop better critical and creative skills required for pursuing their future profession and redesign the curriculum to integrate more relevant, practical skills in the emerging technology and Accounting knowledge areas. In addition, businesses should provide distinctive job training for employees from/with different education backgrounds to help them become more quickly adapted to the job.

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ERDEMİR, Ayhan, and Cemil UYGUR. "Factors Affecting Robotic Surgery and the Learning Curve." Turkiye Klinikleri Journal of Urology 6, no. 1 (2015): 1–9. http://dx.doi.org/10.5336/urology.2014-41987.

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Mohd Salleh, Umi Kalsum, Hutkemri Zulnaidi, and Suzieleez Syrene Abdul Rahim. "FACTORS AFFECTING UNIVERSITY STUDENTS’ LIFELONG LEARNING IN INDONESIA." Malaysian Online Journal of Educational Management 28, no. 1 (December 26, 2019): 82–98. http://dx.doi.org/10.22452/mojem.vol8no1.5.

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Mohd Salleh, Umi Kalsum, Hutkemri Zulnaidi, and Suzieleez Syrene Abdul Rahim. "FACTORS AFFECTING UNIVERSITY STUDENTS’ LIFELONG LEARNING IN INDONESIA." Malaysian Online Journal of Educational Management 8, no. 1 (December 26, 2019): 82–98. http://dx.doi.org/10.22452/mojem/vol8no1.5.

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Mahmood, Shimal Khalid. "Factors Affecting Learning Islamic Science in Developing Countries." International journal of Rural Development, Environment and Health Research 3, no. 5 (2019): 168–76. http://dx.doi.org/10.22161/ijreh.3.5.3.

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34

신동희. "Gender Characteristics of factors affecting students' science learning." Journal of Research in Curriculum Instruction 12, no. 2 (June 2008): 413–56. http://dx.doi.org/10.24231/rici.2008.12.2.413.

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35

Kwakman, Kitty. "Factors affecting teachers’ participation in professional learning activities." Teaching and Teacher Education 19, no. 2 (February 2003): 149–70. http://dx.doi.org/10.1016/s0742-051x(02)00101-4.

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36

Kim-Soon, Ng, Abd Rahman Ahmad, Ng Mei Xin Sirisa, Tan Hui Fang, and Huam Hon Tat. "Behavioral Factors Affecting Intention to Use E-Learning." Advanced Science Letters 22, no. 7 (July 1, 2016): 1853–59. http://dx.doi.org/10.1166/asl.2016.7049.

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37

Micallef, Ricarda, and Reem Kayyali. "Factors affecting a face-to-face learning event." International Journal of Pharmacy Practice 26, no. 2 (May 17, 2017): 183–90. http://dx.doi.org/10.1111/ijpp.12373.

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38

Xu, Hong. "Factors affecting faculty use of learning object repositories." Electronic Library 33, no. 6 (November 2, 2015): 1065–78. http://dx.doi.org/10.1108/el-07-2014-0108.

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Purpose – The purpose of this study was to identify factors that motivate or impede faculty use of learning object repositories (LORs). The unified theory of acceptance and use of technology (UTAUT) served as the theoretical framework for this study. Design/methodology/approach – The study used both quantitative and qualitative approaches to explore two research questions relating to factors affecting faculty use of LORs. Research subjects were faculty users in two- or four-year colleges or universities from two LORs: Orange Grove and Wisconsin Online Resource Center (Wisc-Online). Two phases of the study were conducted. Phase I of the study collected data by semi-structured interviews, and data were analyzed by a content analysis method. Based on the results of Phase I, Phase II collected data by a survey instrument, and data were analyzed by descriptive statistics and analysis of variance. Findings – The study identified 22 factors as motivators for faculty use of LORs and 13 factors as barriers for faculty use of LORs. Research limitations/implications – The research policies of Orange Grove and Wisc-Online limited the selection of study participants. Lack of a random sample and a small sample size limited the generalizability of the results and findings of the study. However, as an exploratory research, the results and findings of the study are still valuable for LOR builders and managers to get a better understanding of factors affecting faculty use of LORs, and to develop strategies to recruit more faculty members to use LORs. Practical implications – The findings and results of the study can inform designers and managers of LORs about what positively or negatively influences faculty use of LORs, and serve as a basis to develop strategies to recruit faculty members to use LORs. Originality/value – First, this study identified the factors that motivate or impede faculty use of LORs from actual faculty users’ perspectives, so these factors more accurately reflect LORs’ values to faculty in teaching and course design and the barriers for faculty use of LORs in a practical environment. Second, this study is among the first known to explore these factors using UTAUT as the theoretical framework, and the results of the study also validate UTAUT in the context of faculty use of LORs.

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Pollitt, A. B., J. W. Searl, and A. S. El Sheikh. "Factors affecting girls' learning of mathematics in Sudan." Educational Studies in Mathematics 18, no. 4 (November 1987): 439–44. http://dx.doi.org/10.1007/bf00240989.

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Nurul Indah Asri, Galuh, and Firdaus Adrianto Adrianto. "FACTORS AFFECTING BLIND STUDENTS’ ENGAGEMENT IN LEARNING ENGLISH." Education of English as Foreign Language 4, no. 2 (July 1, 2021): 58–65. http://dx.doi.org/10.21776/ub.educafl.2021.004.02.01.

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Universitas Brawijaya (UB) with the assistance of Pusat Studi dan Layanan Disabilitas (PSLD) have implemented an inclusive education environment, as the need for equal education chance for different abilities Indonesians. There is an assumption that engagement from a combination of language learning or learning language’s cognitive, social, and affective aspects can affect the learning process and academic achievement of a special need student. To reach the research objective, interview sessions and classroom observations session were aimed at measuring the students' language learning engagement based on three-domains; cognitive, affective and social, in students’ perspective and ongoing activities. This research shows fluctuate results based on the interviews and observations data of two blind students. The main engaged factors found are positive teaching approaches and attitudes, also both students’ learning autonomy.

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Kosasih, Marcella Melly. "Factors Affecting Indonesian Students in Learning English Pronunciation." International Research in Higher Education 6, no. 3 (August 27, 2021): 13. http://dx.doi.org/10.5430/irhe.v6n3p13.

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Oral fluency is very important in communication. It involves different skills like grammar and vocabulary. Pronunciation, however, is very significant for successful communication. Many learners of the English language have major problems with English pronunciation even after years of learning the language. Certain factors affect the learners’ pronunciation learning and the present study aims to identify the factors that affect Indonesian students in learning pronunciation of English as a foreign language. Participants were 45 first-semester students who enrolled in a Pronunciation class in a private university in West Java, Indonesia. A mixed method was used to gather data. The researcher used a quantitative method by using a questionnaire to identify the factors and a qualitative method by using observation, records, and note-taking to identify the problems students have in learning pronunciation. Data were collected, categorized, and analyzed. From this study, it is identified that the factors influencing the students’ pronunciation accuracy were native language interference, phonological awareness, pronunciation instruction, corrective feedback, and the most important of all was the response students gave to achieve their goal. The researcher also suggests some strategies to help students overcome the problems concerning those factors. It is hoped that by knowing the factors affecting students in learning English pronunciation, the teachers can help students to have English pronunciation accuracy.

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Tunji-Olayeni, P. P. F., K. Kajimo – Shakantu, T. O. Ayodele, and KZ Emmanuela. "Factors Affecting Students’ Learning in Civil Engineering Measurement." IOP Conference Series: Earth and Environmental Science 654, no. 1 (February 1, 2021): 012033. http://dx.doi.org/10.1088/1755-1315/654/1/012033.

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43

Slameto, S. "CRITICAL THINKING AND ITS AFFECTING FACTORS." Jurnal Penelitian Humaniora 18, no. 2 (September 12, 2017): 1. http://dx.doi.org/10.23917/humaniora.v18i2.5187.

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The objectives of this research were to measure the success rate achieved by the alumni of Open/Distance Learning (O/DL), the Bachelor Education In-service Teachers Program (BEITP), Staya Jacana Christian University(SWCU), Salatiga in their critical thinking habit that lead to their success, and to find factors which determined their critical thinking habit. The factors concerned were student factor (learning motivation, alumni’s readiness to enter ICT community, prerequisite) or teacher factor (teacher’s ability in creating and using a new instructional context). This quantitative research belongs to the causality ex-post facto research. The data source was one class of O/ DL, the BEITP, SWCUstudents, who were chosen out of four classes, as many as 32 alumni in the academic year 2015/2016. Data were screened using a self-rating scale, which consisted of 40 items tested valid and reliable, and then reduced to 5 variablas. The BEITP, SWCU Salatiga had graduated most of its alumni who owned critical thinking habit at a high rate. The critical thinking habit was affected by the instructional contexts which enabled a new situation (Model 1), alumni’s readiness to enter the ICT community (Model 2), pre-requisite, i.e., mastery of previous lecture materials (Model 3), and student’s learning motivation (Model 4) to reach 81%. The alumni’s critical thinking habit of 51.20% was determined by the teacher’s role in developing instructional contexts which made a new situation possible. This finding was useful for educational quality management for the effectiveness and productivity of higher education, which should have been focused on the teacher in developing an instructional strategy based on context, alumni readiness to enter the ICT community, prerequisite, and student’s learning motivation.

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Thien NGO, Van. "Factors Affecting Students’ Learning Satisfaction: Case Study in Learning Physics Courses." International Journal of Education, Training and Learning 5, no. 1 (2021): 1–10. http://dx.doi.org/10.33094/6.2017.2021.51.1.10.

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45

Seo, Chang-Gab, and Seok-Yong Lee. "An Empirical Study on the Factors Affecting e-Learning Learners Satisfaction." Journal of Information Systems 18, no. 3 (September 1, 2009): 1–25. http://dx.doi.org/10.5859/kais.2009.18.3.001.

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46

Ibrahim, Abdul-Wahab. "Correlate of Factors Affecting Effective Learning of English Language among Undergraduate Students in Northwest Nigeria." Journal of Advanced Research in English & Education 03, no. 03 (October 15, 2018): 6–13. http://dx.doi.org/10.24321/2456.4370.201807.

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47

Bown, Jennifer. "Locus of Learning and Affective Strategy Use: Two Factors Affecting Success in Self-Instructed Language Learning." Foreign Language Annals 39, no. 4 (December 2006): 640–59. http://dx.doi.org/10.1111/j.1944-9720.2006.tb02281.x.

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48

Gurer, Melih Derya, and Seyfullah Tokumaci. "Factors Affecting Engineering Students’ Achievement in Computer Programming." International Journal of Computer Science Education in Schools 3, no. 4 (May 5, 2020): 23–34. http://dx.doi.org/10.21585/ijcses.v3i4.74.

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Literature indicated that attitude toward programming, programming self-efficacy, gender, and students’ department has been related to achievement in computer programming. However, there is a need for further studies investigating to what extent these factors explain programming achievement in a model. This study aimed to investigate the effects of programming self-efficacy, attitude towards programming, gender, and students’ department on their perceived learning. A correlational study design was adopted for this study. The sample of the study was 742 students of an engineering faculty at a state university inTurkey. To collect data, Programming Self-Efficacy Scale, Computer Programming Attitude Scale, and Perceived Learning Scale were used. To analyze data, descriptive statistics e.g. mean and standard deviation, and Pearson Correlation tests were administered. In addition, to determine the factors affecting perceived learning, multiple regression analysis was employed. The results indicated that the engineering faculty students’ attitudes towards programming, programming self-efficacy and perceived learning were at high level. In addition, significant correlations between perceived learning and predictive variables were found. Finally, it was concluded that gender, attitude towards programming and programming self-efficacy significantly predicted perceived learning. The results of the study provide a deeper understanding of how students’ learning was affected in programming courses.

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Hammouri, Qais, and Emad Abu-Shanab. "Exploring Factors Affecting Users' Satisfaction Toward E-Learning Systems." International Journal of Information and Communication Technology Education 14, no. 1 (January 2018): 44–57. http://dx.doi.org/10.4018/ijicte.2018010104.

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E-learning is emerging as the new phenomenon of modern education. Universities are adopting e-learning as a strategy for the improving the teaching/learning process. The primary question addressed in this paper is related to the factors influencing the adoption of e-learning. An integrated model was used to explore the factors influencing students' satisfaction with e-learning in Jordan. The model adopted five variables from the technology acceptance model, Delone and McLean model and the social cognitive theory to predict students' satisfaction with e-learning. A sample of 386 students was utilized and an instrument with 30 items was used. Results indicated that perceived ease of use, perceived usefulness, system quality, information quality, and computer self-efficacy are major factors influencing students' satisfaction. The coefficient of determination estimated to be 0.498, and yielded a full support of all proposed hypotheses. Conclusions and future work are reported at the end of this study.

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Folami, Ahmadu Bolanle, Ahmad Saeed Riaz, and Majeed Olayori Musolihu. "Critical Environmental Factors Affecting Learning in College of Education." EduLine: Journal of Education and Learning Innovation 1, no. 1 (March 24, 2021): 52–58. http://dx.doi.org/10.35877/454ri.eduline400.

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Learning environment in modern day Nigeria has not been friendly with both learners and teachers and this has created a lot of vacuum in the learning process. This study discusses the critical factors affecting learning environment. This study identifies certain factors like environmental, social, intellectual that inhibit the effective participatory of students in a learning environment. The study adopted triangulate research method and about 227 participants were involved in the administration of the questionnaire for study. The data collected from the questionnaires administered were presented through frequency percentage counts. Chi-square(X2) analysis was used for testing the hypotheses to justify the outcome of the study. Our findings, shows how much learning influence environments have on the students’ success. It also reveal that students who learn in conducive environments effectively receive the adequate knowledge and performance required of them. The study concludes that critical factors such as cultural, social, environmental etc. have negative influence on the learning environment. We recommended that learning environment in nook and crannies of the world should be given appropriate facilities and attention to make it a conducive environment for learners and as well pane way for students to have freedom to express their feeling and connections of knowledge passed across by the educators.

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