The Impact of Motivation on MOOC Retention Rates: A Systematic Review

Zakaria Alj, Anas Bouayad

Abstract


This systematic review investigates the effectiveness of motivational strategies on learner engagement and retention rates in Massive Open Online Courses (MOOCs). Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we analyzed 140 studies published between 2014 and 2023 from key academic databases. The objective was to identify and evaluate motivational strategies that significantly reduce MOOC dropout rates. Our findings reveal that personalized learning, interactive content, and peer collaboration are strongly correlated with increased learner engagement and persistence. These strategies align well with learners' intrinsic goals, enhancing their educational experience and adherence to courses. The review also identifies gaps, such as the need for longitudinal studies and culturally tailored motivational strategies, offering a refined agenda for future research in MOOC education. This study contributes to the field by systematically synthesizing existing research, providing new insights into effective educational strategies, and highlighting areas for improvement in MOOC design and implementation.

 

Doi: 10.28991/ESJ-2024-SIED1-08

Full Text: PDF


Keywords


MOOC; Dropout; Motivation; Engagement; Review; Design.

References


Hokanson, B. (2022). New approaches on education technologies: A global perspective for digital transformation. Journal of Educational Technology and Online Learning, 5(4), 775–780. doi:10.31681/jetol.1160872.

Wang, Y., Fikes, T. G., & Pettyjohn, P. (2018). Open Scale Courses: Exploring Access and Opportunity for Less-Educated Learners. 2018 Learning With MOOCS (LWMOOCS), Madrid, Spain. doi:10.1109/LWMOOCS.2018.8534667.

Azhar, K. A., Iqbal, N., Shah, Z., & Ahmed, H. (2023). Understanding high dropout rates in MOOCs – a qualitative case study from Pakistan. Innovations in Education and Teaching International, 61(4), 764–778. doi:10.1080/14703297.2023.2200753.

Dalipi, F., Imran, A. S., & Kastrati, Z. (2018). MOOC dropout prediction using machine learning techniques: Review and research challenges. 2018 IEEE Global Engineering Education Conference (EDUCON), Spain. doi:10.1109/educon.2018.8363340.

Aldowah, H., Al-Samarraie, H., Alzahrani, A. I., & Alalwan, N. (2019). Factors affecting student dropout in MOOCs: a cause and effect decision‐making model. Journal of Computing in Higher Education, 32(2), 429–454. doi:10.1007/s12528-019-09241-y.

Goopio, J., & Cheung, C. (2021). The MOOC dropout phenomenon and retention strategies. Journal of Teaching in Travel & Tourism, 21(2), 177–197. doi:10.1080/15313220.2020.1809050.

Hakami, N., White, S., & Chakaveh, S. (2017). Motivational Factors that Influence the use of MOOCs: Learners’ Perspectives - A Systematic Literature Review. Proceedings of the 9th International Conference on Computer Supported Education, Porto, Portugal. doi:10.5220/0006259503230331.

Xiong, Y., Li, H., Kornhaber, M. L., Suen, H. K., Pursel, B., & Goins, D. D. (2015). Examining the relations among student motivation, engagement, and retention in a MOOC: A structural equation modeling approach. Global Education Review, 2(3), 23-33.

Kizilcec, R. F., Pérez-Sanagustín, M., & Maldonado, J. J. (2017). Self-regulated learning strategies predict learner behavior and goal attainment in Massive Open Online Courses. Computers & Education, 104, 18–33. doi:10.1016/j.compedu.2016.10.001.

Zhu, M., Sari, A. R., & Lee, M. M. (2020). A comprehensive systematic review of MOOC research: Research techniques, topics, and trends from 2009 to 2019. Educational Technology Research and Development, 68(4), 1685–1710. doi:10.1007/s11423-020-09798-x.

Wang, X., Wen, M., & Rosé, C. P. (2016). Towards triggering higher-order thinking behaviors in MOOCs. Proceedings of the Sixth International Conference on Learning Analytics & Knowledge, 398 - 407. doi:10.1145/2883851.2883964.

Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. The BMJ, 372, 71. doi:10.1136/bmj.n71.

Abdullatif, H., & Velázquez-Iturbide, J. Á. (2020). Relationship between motivations, personality traits and intention to continue using MOOCs. Education and Information Technologies, 25(5), 4417–4435. doi:10.1007/s10639-020-10161-z.

Alario-Hoyos, C., Estévez-Ayres, I., Pérez-Sanagustín, M., Kloos, C. D., & Fernández-Panadero, C. (2017). Understanding learners’ motivation and learning strategies in MOOCs. International Review of Research in Open and Distributed Learning, 18(3), 119–137. doi:10.19173/irrodl.v18i3.2996.

Alraimi, K. M., Zo, H., & Ciganek, A. P. (2015). Understanding the MOOCs continuance: The role of openness and reputation. Computers & Education, 80, 28–38. doi:10.1016/j.compedu.2014.08.006.

Barak, M., Watted, A., & Haick, H. (2016). Motivation to learn in massive open online courses: Examining aspects of language and social engagement. Computers & Education, 94, 49–60. doi:10.1016/j.compedu.2015.11.010.

Bayeck, R. Y. (2016). Exploratory study of MOOC learners’ demographics and motivation: The case of students involved in groups. Open Praxis, 8(3), 223. doi:10.5944/openpraxis.8.3.282.

Bonk, C. J., & Lee, M. M. (2017). Motivations, Achievements, and Challenges of Self-Directed Informal Learners in Open Educational Environments and MOOCs. Journal of Learning for Development, 4(1), 36–57. doi:10.56059/jl4d.v4i1.195.

Brooker, A., Corrin, L., De Barba, P., Lodge, J., & Kennedy, G. (2018). A tale of two MOOCs: How student motivation and participation predict learning outcomes in different MOOCs. Australasian Journal of Educational Technology, 34(1), 73-87. doi:10.14742/ajet.3237.

Buhr, E. E., Daniels, L. M., & Goegan, L. D. (2019). Cognitive appraisals mediate relationships between two basic psychological needs and emotions in a massive open online course. Computers in Human Behavior, 96, 85–94. doi:10.1016/j.chb.2019.02.009.

Carrera, J., & Ramírez-Hernández, D. (2018). Innovative education in MOOC for sustainability: Learnings and motivations. Sustainability (Switzerland), 10(9), 2990. doi:10.3390/su10092990.

Reparaz, C., Aznárez-Sanado, M., & Mendoza, G. (2020). Self-regulation of learning and MOOC retention. Computers in Human Behavior, 111, 106423. doi:10.1016/j.chb.2020.106423.

Chang, R. I., Hung, Y. H., & Lin, C. F. (2015). Survey of learning experiences and influence of learning style preferences on user intentions regarding MOOCs. British Journal of Educational Technology, 46(3), 528–541. doi:10.1111/bjet.12275.

Deshpande, A., & Chukhlomin, V. (2017). What Makes a Good MOOC: A Field Study of Factors Impacting Student Motivation to Learn. American Journal of Distance Education, 31(4), 275–293. doi:10.1080/08923647.2017.1377513.

Doo, M. Y., Tang, Y., Bonk, C. J., & Zhu, M. (2020). MOOC instructor motivation and career development. Distance Education, 41(1), 26–47. doi:10.1080/01587919.2020.1724770.

El Said, G. R. (2017). Understanding How Learners Use Massive Open Online Courses and Why They Drop Out. Journal of Educational Computing Research, 55(5), 724–752. doi:10.1177/0735633116681302.

Eriksson, T., Adawi, T., & Stöhr, C. (2017). “Time is the bottleneck”: a qualitative study exploring why learners drop out of MOOCs. Journal of Computing in Higher Education, 29(1), 133–146. doi:10.1007/s12528-016-9127-8.

Moreira-Mora, T., & Espinoza-Guzmán, J. (2016). Initial evidence to validate an instructional design-derived evaluation scale in higher education programs. International Journal of Educational Technology in Higher Education, 13(1), 11. doi:10.1186/s41239-016-0007-0.

Gomez-Zermeno, M. G., & Aleman De La Garza, L. (2016). Research Analysis on Mooc Course Dropout and Retention Rates. Turkish Online Journal of Distance Education. doi:10.17718/tojde.23429.

Greene, J. A., Oswald, C. A., & Pomerantz, J. (2015). Predictors of Retention and Achievement in a Massive Open Online Course. American Educational Research Journal, 52(5), 925–955. doi:10.3102/0002831215584621.

Gregori, E. B., Zhang, J., Galván-Fernández, C., & Fernández-Navarro, F. de A. (2018). Learner support in MOOCs: Identifying variables linked to completion. Computers and Education, 122, 153–168. doi:10.1016/j.compedu.2018.03.014.

Hone, K. S., & El Said, G. R. (2016). Exploring the factors affecting MOOC retention: A survey study. Computers & Education, 98, 157–168. doi:10.1016/j.compedu.2016.03.016.

Howarth, J. P., D’Alessandro, S., Johnson, L., & White, L. (2016). Learner motivation for MOOC registration and the role of MOOCs as a university ‘taster.’ International Journal of Lifelong Education, 35(1), 74–85. doi:10.1080/02601370.2015.1122667.

James, J. L. (2022). Students as Stakeholders: Understanding Expectations Can Increase Student Retention. Journal of College Student Retention: Research, Theory & Practice, 24(1), 20–42. doi:10.1177/1521025119898844.

Joo, Y. J., So, H. J., & Kim, N. H. (2018). Examination of relationships among students’ self-determination, technology acceptance, satisfaction, and continuance intention to use K-MOOCs. Computers & Education, 122, 260–272. doi:10.1016/j.compedu.2018.01.003.

Jung, Y., & Lee, J. (2018). Learning Engagement and Persistence in Massive Open Online Courses (MOOCS). Computers and Education, 122, 9–22. doi:10.1016/j.compedu.2018.02.013.

Khan, I. U., Hameed, Z., Yu, Y., Islam, T., Sheikh, Z., & Khan, S. U. (2018). Predicting the acceptance of MOOCs in a developing country: Application of task-technology fit model, social motivation, and self-determination theory. Telematics and Informatics, 35(4), 964–978. doi:10.1016/j.tele.2017.09.009.

Kim, T., Yang, M., Bae, J., Min, B., Lee, I., & Kim, J. (2017). Escape from infinite freedom: Effects of constraining user freedom on the prevention of dropout in an online learning context. Computers in Human Behavior, 66, 217–231. doi:10.1016/j.chb.2016.09.019.

Kyewski, E., & Krämer, N. C. (2018). To gamify or not to gamify? An experimental field study of the influence of badges on motivation, activity, and performance in an online learning course. Computers and Education, 118, 25–37. doi:10.1016/j.compedu.2017.11.006.

Li, Q., & Baker, R. (2018). The different relationships between engagement and outcomes across participant subgroups in Massive Open Online Courses. Computers and Education, 127(April 2017), 41–65. doi:10.1016/j.compedu.2018.08.005.

Luik, P., Suviste, R., Lepp, M., Palts, T., Tõnisson, E., Säde, M., & Papli, K. (2017). What motivates enrolment in programming MOOCs? British Journal of Educational Technology, 50(1), 153–165. doi:10.1111/bjet.12600.

Maya-Jariego, I., Holgado, D., González-Tinoco, E., Castaño-Muñoz, J., & Punie, Y. (2020). Typology of motivation and learning intentions of users in MOOCs: the MOOCKNOWLEDGE study. Educational Technology Research and Development, 68(1), 203–224. doi:10.1007/s11423-019-09682-3.

Ortega-Arranz, A., Bote-Lorenzo, M. L., Asensio-Pérez, J. I., Martínez-Monés, A., Gómez-Sánchez, E., & Dimitriadis, Y. (2019). To reward and beyond: Analyzing the effect of reward-based strategies in a MOOC. Computers & Education, 142, 103639. doi:10.1016/j.compedu.2019.103639.

Petronzi, D., & Hadi, M. (2016). Exploring the Factors Associated with MOOC Engagement, Retention and the Wider Benefits for Learners. European Journal of Open, Distance and E-Learning, 19(2), 112–129. doi:10.1515/eurodl-2016-0011.

Salmon, G., Pechenkina, E., Chase, A. M., & Ross, B. (2017). Designing Massive Open Online Courses to take account of participant motivations and expectations. British Journal of Educational Technology, 48(6), 1284–1294. doi:10.1111/bjet.12497.

Shao, Z. (2018). Examining the impact mechanism of social psychological motivations on individuals’ continuance intention of MOOCs. Internet Research, 28(1), 232–250. doi:10.1108/intr-11-2016-0335.

Shapiro, H. B., Lee, C. H., Wyman Roth, N. E., Li, K., Çetinkaya-Rundel, M., & Canelas, D. A. (2017). Understanding the massive open online course (MOOC) student experience: An examination of attitudes, motivations, and barriers. Computers & Education, 110, 35–50. doi:10.1016/j.compedu.2017.03.003.

Sujatha, R., & Kavitha, D. (2018). Learner retention in MOOC environment: Analyzing the role of motivation, self-efficacy and perceived effectiveness. International Journal of Education and Development Using ICT, 14(2), 62-74.

Sun, Y., Ni, L., Zhao, Y., Shen, X. L., & Wang, N. (2019). Understanding students’ engagement in MOOCs: An integration of self-determination theory and theory of relationship quality. British Journal of Educational Technology, 50(6), 3156–3174. doi:10.1111/bjet.12724.

Chaw, L. Y., & Tang, C. M. (2019). Driving high inclination to complete massive open online courses (MOOCs): Motivation and engagement factors for learners. Electronic Journal of E-Learning, 17(2), 118–130. doi:10.34190/JEL.17.2.05.

Tsai, Y., Lin, C., Hong, J., & Tai, K. (2018). The effects of metacognition on online learning interest and continuance to learn with MOOCs. Computers & Education, 121, 18–29. doi:10.1016/j.compedu.2018.02.011.

Uchidiuno, J. O., Ogan, A., Yarzebinski, E., & Hammer, J. (2018). Going Global: Understanding English Language Learners’ Student Motivation in English-Language MOOCs. International Journal of Artificial Intelligence in Education, 28(4), 528–552. doi:10.1007/s40593-017-0159-7.

Wang, Y., & Baker, R. (2015). Content or platform: Why do students complete MOOCs. MERLOT Journal of Online Learning and Teaching, 11(1), 17-30.

Wang, Y., & Baker, R. (2018). Grit and intention: Why do learners complete MOOCs? The International Review of Research in Open and Distributed Learning, 19(3), 20–42.

Watted, A., & Barak, M. (2018). Motivating factors of MOOC completers: Comparing between university-affiliated students and general participants. Internet and Higher Education, 37, 11–20. doi:10.1016/j.iheduc.2017.12.001.

Wu, B., & Chen, X. (2017). Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model. Computers in Human Behavior, 67, 221–232. doi:10.1016/j.chb.2016.10.028.

Xing, B., Zhang, L., Gao, J., Yu, R., & Lyu, R. (2016). Barrier-free affective communication in MOOC study by analyzing pupil diameter variation. SIGGRAPH ASIA 2016 Symposium on Education. doi:10.1145/2993352.2993362.

Zhou, M. (2016). Chinese university students’ acceptance of MOOCs: A self-determination perspective. Computers & Education, 92–93, 194–203. doi:10.1016/j.compedu.2015.10.012.

Zhao, Y., Wang, A., & Sun, Y. (2020). Technological environment, virtual experience, and MOOC continuance: A stimulus–organism–response perspective. Computers & Education, 144, 103721. doi:10.1016/j.compedu.2019.103721.

Alharbi, K., Alrajhi, L., Cristea, A. I., Bittencourt, I. I., Isotani, S., & James, A. (2020). Data-Driven Analysis of Engagement in Gamified Learning Environments: A Methodology for Real-Time Measurement of MOOCs. Intelligent Tutoring Systems. ITS 2020. Lecture Notes in Computer Science, 12149, Springer, Cham, Switzerland. doi:10.1007/978-3-030-49663-0_18.

Antonaci, A., Klemke, R., Lataster, J., Kreijns, K., & Specht, M. (2019). Gamification of MOOCs Adopting Social Presence and Sense of Community to Increase User’s Engagement: An Experimental Study. Transforming Learning with Meaningful Technologies. EC-TEL 2019. Lecture Notes in Computer Science, Vol. 11722, Springer, Cham, Switzerland. doi:10.1007/978-3-030-29736-7_13.

Anutariya, C., & Thongsuntia, W. (2019). MOOC Design and Learners Engagement Analysis: A Learning Analytics Approach. 2019 International Conference on Sustainable Information Engineering and Technology (SIET), Lombok, Indonesia. doi:10.1109/siet48054.2019.8986057.

Appiah-Kubi, K., & Rowland, D. (2016). PEER Support In MOOCs. Proceedings of the Third (2016) ACM Conference on Learning @ Scale. doi:10.1145/2876034.2893423.

Baek, J., & Shore, J. (2016). Promoting Student Engagement in MOOCs. Proceedings of the Third (2016) ACM Conference on Learning @ Scale. doi:10.1145/2876034.2893437.

Balasooriya, I., Rodríguez, M. E., & Mor, E. (2018). Assessment of Engagement: Using Microlevel Student Engagement as a Form of Continuous Assessment. Communications in Computer and Information Science, 150–162. doi:10.1007/978-3-319-97807-9_12.

Bonafini, F. C., Chae, C., Park, E., & Jablokow, K. W. (2017). How much does student engagement with videos and forums in a MOOC affect their achievement? Online Learning Journal, 21(4), 223–240. doi:10.24059/olj.v21i4.1270.

Borrás-Gené, O., Martínez-Núñez, M., & Martín-Fernández, L. (2019). Enhancing fun through gamification to improve engagement in MOOC. Informatics, 6(3), 1–20. doi:10.3390/informatics6030028.

Bote-Lorenzo, M. L., & Gómez-Sánchez, E. (2017). Predicting the decrease of engagement indicators in a MOOC. Proceedings of the Seventh International Learning Analytics & Knowledge Conference. doi:10.1145/3027385.3027387.

Brady, K., Fisher, D., & Narasimham, G. (2016). Exploring the effects of lightweight social incentives on learner performance in MOOCs. L@S 2016 - Proceedings of the 3rd 2016 ACM Conference on Learning at Scale, 297–300. doi:10.1145/2876034.2893438.

Brunskill, E., Zimmaro, D., & Thille, C. (2018). Exploring the impact of the default option on student engagement and performance in a statistics MOOC. Proceedings of the Fifth Annual ACM Conference on Learning at Scale, 1-4. doi:10.1145/3231644.3231692.

Cassidy, D., Breakwell, N., & Bailey, J. (2014). Keeping them clicking: promoting student engagement in MOOC design. The All Ireland Journal of Teaching and Learning in Higher Education, 6(2), 1-15.

Chang, J. W., & Wei, H. Y. (2016). Exploring engaging gamification mechanics in massive online open courses. Journal of Educational Technology & Society, 19(2), 177-203.

Chen, G., Davis, D., Lin, J., Hauff, C., & Houben, G.-J. (2016). Beyond the MOOC platform. Proceedings of the 8th ACM Conference on Web Science. doi:10.1145/2908131.2908145.

Coetzee, D., Fox, A., Hearst, M. A., & Hartmann, B. (2014). Should your mooc forum use a reputation system? Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW, 1176–1187. doi:10.1145/2531602.2531657.

Coffrin, C., Corrin, L., de Barba, P., & Kennedy, G. (2014). Visualizing patterns of student engagement and performance in MOOCs. Proceedings of the Fourth International Conference on Learning Analytics And Knowledge, 83-92. doi:10.1145/2567574.2567586.

Cook, S., Bingham, P., Reid, S., & Wang, X. (2015). Going'massive': Learner engagement in a MOOC environment. THETA 2015-Create, Connect, Consume-Innovating today for tomorrow, 11-13 May 2015, Gold Coast, Australia.

Crosslin, M., Dellinger, J. T., Joksimović, S., Kovanović, V., & Gašević, D. (2018). Customizable modalities for individualized learning: Examining patterns of engagement in dual-layer MOOCS. Online Learning Journal, 22(1), 19–38. doi:10.24059/olj.v22i1.1080.

Crues, R. W., Bosch, N., Perry, M., Angrave, L., Shaik, N., & Bhat, S. (2018). Refocusing the lens on engagement in MOOCs. Proceedings of the Fifth Annual ACM Conference on Learning at Scale, 1-10. doi:10.1145/3231644.3231658.

Davis, D., Jivet, I., Kizilcec, R. F., Chen, G., Hauff, C., & Houben, G.-J. (2017). Follow the successful crowd. Proceedings of the Seventh International Learning Analytics & Knowledge Conference, 454 - 463. doi:10.1145/3027385.3027411.

De Freitas, S. I., Morgan, J., & Gibson, D. (2015). Will MOOCs transform learning and teaching in higher education? Engagement and course retention in online learning provision. British Journal of Educational Technology, 46(3), 455–471. doi:10.1111/bjet.12268.

Deng, R., Benckendorff, P., & Gannaway, D. (2020). Learner engagement in MOOCs: Scale development and validation. British Journal of Educational Technology, 51(1), 245–262. doi:10.1111/bjet.12810.

Deng, R., Benckendorff, P., & Gannaway, D. (2020). Linking learner factors, teaching context, and engagement patterns with MOOC learning outcomes. Journal of Computer Assisted Learning, 36(5), 688–708. doi:10.1111/jcal.12437

Dubbaka, A., & Gopalan, A. (2020). Detecting Learner Engagement in MOOCs using Automatic Facial Expression Recognition. 2020 IEEE Global Engineering Education Conference (EDUCON), Porto, Portugal. doi:10.1109/educon45650.2020.9125149.

Ferguson, R., & Clow, D. (2016). Consistent Commitment: Patterns of Engagement across Time in Massive Open Online Courses (MOOCs). Journal of Learning Analytics, 2(3), 55–80. doi:10.18608/jla.2015.23.5.

Ferguson, R., & Clow, D. (2015). Examining engagement. Proceedings of the Fifth International Conference on Learning Analytics And Knowledge, 51 - 58. doi:10.1145/2723576.2723606.

Ferguson, R., Clow, D., Beale, R., Cooper, A. J., Morris, N., Bayne, S., & Woodgate, A. (2015). Moving Through MOOCS: Pedagogy, Learning Design and Patterns of Engagement. Lecture Notes in Computer Science, 70–84, Springer, Cham, Switzerland. doi:10.1007/978-3-319-24258-3_6.

Floratos, N., Guasch, T., & Espasa, A. (2015). Recommendations on Formative Assessment and Feedback Practices for stronger engagement in MOOCs. Open Praxis, 7(2), 141. doi:10.5944/openpraxis.7.2.194.

Gallego-Romero, J. M., Alario-Hoyos, C., Estévez-Ayres, I., & Delgado Kloos, C. (2020). Analyzing learners’ engagement and behavior in MOOCs on programming with the Codeboard IDE. Educational Technology Research and Development, 68(5), 2505–2528. doi:10.1007/s11423-020-09773-6.

Goldberg, L. R., Bell, E., King, C., O’Mara, C., McInerney, F., Robinson, A., & Vickers, J. (2015). Relationship between participants’ level of education and engagement in their completion of the Understanding Dementia Massive Open Online Course Approaches to teaching and learning. BMC Medical Education, 15(1), 60. doi:10.1186/s12909-015-0344-z.

Gong, L., Liu, Y., & Zhao, W. (2019). Dynamics of Emotional States and Their Relationship with Learning Outcomes during Learning Python with MOOC. Proceedings of the 2019 7th International Conference on Information and Education Technology, 71 - 76. doi:10.1145/3323771.3323821.

Guo, P. J., Kim, J., & Rubin, R. (2014). How video production affects student engagement. Proceedings of the First ACM Conference on Learning @ Scale Conference, 41 - 50. doi:10.1145/2556325.2566239.

Hew, K. F. (2016). Promoting engagement in online courses: What strategies can we learn from three highly rated MOOCS. British Journal of Educational Technology, 47(2), 320–341. doi:10.1111/bjet.12235.

Houston, S. L., Brady, K., Narasimham, G., & Fisher, D. (2017). Pass the Idea Please. Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale, 295 - 298. doi:10.1145/3051457.3054008.

Hu, Y., Donald, C., Giacaman, N., & Zhu, Z. (2020). Towards automated analysis of cognitive presence in MOOC discussions. Proceedings of the Tenth International Conference on Learning Analytics & Knowledge, 135-140. doi:10.1145/3375462.3375473.

Huang, J., Dasgupta, A., Ghosh, A., Manning, J., & Sanders, M. (2014). Superposter behavior in MOOC forums. Proceedings of the First ACM Conference on Learning @ Scale Conference. doi:10.1145/2556325.2566249.

Kaveri, A., Gunasekar, S., Gupta, D., & Pratap, M. (2016). Decoding Engagement in MOOCs: An Indian Learner Perspective. 2016 IEEE Eighth International Conference on Technology for Education (T4E). doi:10.1109/t4e.2016.027.

Khalil, M., Ebner, M., & Admiraal, W. (2017). How can gamification improve MOOC student engagement. Proceedings of the 11th European Conference on Games Based Learning, ECGBL, 5-6 October, 2017, Graz, Austria.

Kizilcec, R. F., Davis, G. M., & Cohen, G. L. (2017). Towards Equal Opportunities in MOOCs. Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale, 121 - 130. doi:10.1145/3051457.3051460.

Labarthe, H., Bouchet, F., Bachelet, R., & Yacef, K. (2016, June). Does a peer recommender foster students' engagement in MOOCs?. 9th international conference on educational data mining, 29 June-2July 2016, Raleigh, United States.

Min, L., & Foon, H. K. (2019). Self-Regulated Learning Process in MOOCs. Proceedings of the 2019 4th International Conference on Distance Education and Learning, Shanghai, China. doi:10.1145/3338147.3338161.

Lan, M., & Hew, K. F. (2020). Examining learning engagement in MOOCs: a self-determination theoretical perspective using mixed method. International Journal of Educational Technology in Higher Education, 17(1), 7. doi:10.1186/s41239-020-0179-5.

Bozkurt, A., & Keefer, J. (2017). Participatory learning culture and community formation in connectivist MOOCs. Interactive Learning Environments, 26(6), 776–788. doi:10.1080/10494820.2017.1412988.

Lu, O. H. T., Huang, J. C. H., Huang, A. Y. Q., & Yang, S. J. H. (2017). Applying learning analytics for improving students engagement and learning outcomes in an MOOCs enabled collaborative programming course. Interactive Learning Environments, 25(2), 220–234. doi:10.1080/10494820.2016.1278391.

Milligan, C., Littlejohn, A., & Margaryan, A. (2013). Patterns of engagement in connectivist MOOCs. Journal of Online Learning and Teaching, 9(2), 149-159.

Nelimarkka, M., & Hellas, A. (2018). Social Help-seeking Strategies in a Programming MOOC. Proceedings of the 49th ACM Technical Symposium on Computer Science Education. doi:10.1145/3159450.3159495.

Núñez, M. M., Gené, O. B., & Blanco, Á. F. (2014). Social community in MOOCs. Proceedings of the Second International Conference on Technological Ecosystems for Enhancing Multiculturality. doi:10.1145/2669711.2669893.

Phan, T., McNeil, S. G., & Robin, B. R. (2016). Students’ patterns of engagement and course performance in a Massive Open Online Course. Computers & Education, 95, 36–44. doi:10.1016/j.compedu.2015.11.015.

Qiu, J., Tang, J., Liu, T. X., Gong, J., Zhang, C., Zhang, Q., & Xue, Y. (2016). Modeling and Predicting Learning Behavior in MOOCs. Proceedings of the Ninth ACM International Conference on Web Search and Data Mining. doi:10.1145/2835776.2835842.

Ramesh, A., Goldwasser, D., Huang, B., Daume, H., & Getoor, L. (2020). Interpretable Engagement Models for MOOCs Using Hinge-Loss Markov Random Fields. IEEE Transactions on Learning Technologies, 13(1), 107–122. doi:10.1109/TLT.2018.2889953.

Sharif, M., & Guilland, A. (2015). Massive Open Online Courses-Promoting Engagement Through Means of Gamification. EDULEARN15 Proceedings, 6-8 July, 2015, Barcelona, Spain.

Shi, L., Cristea, A.I. (2018). In-depth Exploration of Engagement Patterns in MOOCs. Web Information Systems Engineering – WISE 2018. WISE 2018, Lecture Notes in Computer Science, vol 11234. Springer, Cham, Switzerland. doi:10.1007/978-3-030-02925-8_28.

Sun, G. X., & Bin, S. (2018). Construction of learning behavioral engagement model for MOOCs platform based on data analysis. Kuram ve Uygulamada Egitim Bilimleri, 18(5), 2206–2216. doi:10.12738/estp.2018.5.120.

Sunar, A. S., White, S., Abdullah, N. A., & Davis, H. C. (2017). How learners’ interactions sustain engagement: A MOOC case study. IEEE Transactions on Learning Technologies, 10(4), 475–487. doi:10.1109/TLT.2016.2633268.

Thaker, K., Carvalho, P., & Koedinger, K. (2019). Comprehension Factor Analysis. Proceedings of the 9th International Conference on Learning Analytics & Knowledge. doi:10.1145/3303772.3303817.

Thornton, S., Riley, C., & Wiltrout, M. E. (2017). Criteria for Video Engagement in a Biology MOOC. Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale. doi:10.1145/3051457.3054007.

Vaibhav, A., & Gupta, P. (2014). Gamification of MOOCs for increasing user engagement. 2014 IEEE International Conference on MOOC, Innovation and Technology in Education (MITE). doi:10.1109/mite.2014.7020290.

Walji, S., Deacon, A., Small, J., & Czerniewicz, L. (2016). Learning through engagement: MOOCs as an emergent form of provision. Distance Education, 37(2), 208–223. doi:10.1080/01587919.2016.1184400.

Wen, M., & Rose, C. P. (2014). Identifying Latent Study Habits by Mining Learner Behavior Patterns in Massive Open Online Courses. Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management. doi:10.1145/2661829.2662033.

Wen, X., Lin, Y.-R., Liu, X., Brusilovsky, P., & BarrÃ-a Pineda, J. (2019). Iterative Discriminant Tensor Factorization for Behavior Comparison in Massive Open Online Courses. The World Wide Web Conference. doi:10.1145/3308558.3313713.

Williams, K. M., Stafford, R. E., Corliss, S. B., & Reilly, E. D. (2018). Examining student characteristics, goals, and engagement in Massive Open Online Courses. Computers & Education, 126, 433–442. doi:10.1016/j.compedu.2018.08.014.

Wise, A. F. (2018). Learning Analytics: Using Data-Informed Decision-Making to Improve Teaching and Learning. Contemporary Technologies in Education, 119–143. doi:10.1007/978-3-319-89680-9_7.

Wong, J.-S., Pursel, B., Divinsky, A., & Jansen, B. J. (2016). An Analysis of Cognitive Learning Context in MOOC Forum Messages. Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems. doi:10.1145/2851581.2892324.

Xiao, X., & Wang, J. (2016). Context and cognitive state triggered interventions for mobile MOOC learning. Proceedings of the 18th ACM International Conference on Multimodal Interaction. doi:10.1145/2993148.2993177.

Zheng, S., Han, K., Rosson, M. B., & Carroll, J. M. (2016). The Role of Social Media in MOOCs. Proceedings of the Third (2016) ACM Conference on Learning @ Scale. doi:10.1145/2876034.2876047.

Zheng, S., Rosson, M. B., Shih, P. C., & Carroll, J. M. (2015). Understanding Student Motivation, Behaviors and Perceptions in MOOCs. Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing. doi:10.1145/2675133.2675217.

Badali, M., Hatami, J., Banihashem, S. K., Rahimi, E., Noroozi, O., & Eslami, Z. (2022). The role of motivation in MOOCs’ retention rates: a systematic literature review. Research and Practice in Technology Enhanced Learning, 17(1). doi:10.1186/s41039-022-00181-3.

Moore, R. L., & Wang, C. (2021). Influence of learner motivational dispositions on MOOC completion. Journal of Computing in Higher Education, 33(1), 121–134. doi:10.1007/s12528-020-09258-8.

Semenova, T. (2022). The role of learners’ motivation in MOOC completion. Open Learning, 37(3), 273–287. doi:10.1080/02680513.2020.1766434.

Xu, R., Sun, Z., Zhao, M., & Fu, M. (2022). How Teaching Presence Facilitate Rural Teachers’ Learning Engagement in MOOC for Teacher Education: The Mediating Effect of Learning Motivation. Proceedings of the 14th International Conference on Education Technology and Computers. doi:10.1145/3572549.3572605.

Estrada-Molina, O., & Fuentes-Cancell, D. R. (2022). Engagement and desertion in MOOCs: Systematic review. Comunicar, 30(70), 107–119. doi:10.3916/C70-2022-09.

Nleme Ze, Y. S., & Molinari, G. (2022). Développement et validation psychométrique d’une échelle de mesure de l’engagement des apprenants dans les forums de discussion des MOOC. Distances et Médiations Des Savoirs, 40(40). doi:10.4000/dms.8538.

Kuo, T. M., Tsai, C. C., & Wang, J. C. (2021). Linking web-based learning self-efficacy and learning engagement in MOOCs: The role of online academic hardiness. The Internet and Higher Education, 51, 100819. doi:10.1016/j.iheduc.2021.100819.

Pérez-Sanagustín, M., Sapunar-Opazo, D., Pérez-Álvarez, R., Hilliger, I., Bey, A., Maldonado-Mahauad, J., & Baier, J. (2021). A MOOC-based flipped experience: Scaffolding SRL strategies improves learners’ time management and engagement. Computer Applications in Engineering Education, 29(4), 750–768. doi:10.1002/cae.22337.

Vázquez, J. A. V., Ramirez-Montoya, M. S., & González, J. R. V. (2021). Psychometric assessment of a tool to evaluate motivation and knowledge of an energy-related topic MOOC. Educational Media International, 58(3), 280–295. doi:10.1080/09523987.2021.1976827.

Rohan, R., Pal, D., Funilkul, S., Chutimaskul, W., & Eamsinvattana, W. (2021). How Gamification Leads to Continued Usage of MOOCs? A Theoretical Perspective. IEEE Access, 9, 108144–108161. doi:10.1109/ACCESS.2021.3102293.

Shao, Z., & Chen, K. (2020). Understanding individuals’ engagement and continuance intention of MOOCs: the effect of interactivity and the role of gender. Internet Research, 31(4), 1262–1289. doi:10.1108/INTR-10-2019-0416.

Cobos, R., & Ruiz-Garcia, J. C. (2021). Improving learner engagement in MOOCs using a learning intervention system: A research study in engineering education. Computer Applications in Engineering Education, 29(4), 733–749. doi:10.1002/cae.22316.

Meekers, L., Kumps, A., Boumazguida, K., Temperman, G., & De Lièvre, B. (2022). Analyse de facteurs qui influencent le choix de parcours des apprenants dans le MOOC « L’innovation pédagogique dont vous êtes le héros ». Distances et Médiations Des Savoirs, 39, 43. doi:10.4000/dms.8268.

Borrella, I., Caballero-Caballero, S., & Ponce-Cueto, E. (2022). Taking action to reduce dropout in MOOCs: Tested interventions. Computers & Education, 179, 104412. doi:10.1016/j.compedu.2021.104412.

Schettino, G., & Capone, V. (2022). Learning Design Strategies in MOOCs for Physicians’ Training: A Scoping Review. International Journal of Environmental Research and Public Health, 19(21), 14247. doi:10.3390/ijerph192114247.

Yu, Z., Xu, W., & Sukjairungwattana, P. (2022). A meta-analysis of eight factors influencing MOOC-based learning outcomes across the world. Interactive Learning Environments, 32(2), 707–726. doi:10.1080/10494820.2022.2096641.

Romero-Frías, E., Arquero, J. L., & del Barrio-García, S. (2023). Exploring how student motivation relates to acceptance and participation in MOOCs. Interactive Learning Environments, 31(1), 480–496. doi:10.1080/10494820.2020.1799020.

Wei, X., Saab, N., & Admiraal, W. (2023). Do learners share the same perceived learning outcomes in MOOCs? Identifying the role of motivation, perceived learning support, learning engagement, and self-regulated learning strategies. The Internet and Higher Education, 56, 100880. doi:10.1016/j.iheduc.2022.100880.

Huang, A. Y. Q., Lu, O. H. T., & Yang, S. J. H. (2023). Effects of artificial Intelligence–Enabled personalized recommendations on learners’ learning engagement, motivation, and outcomes in a flipped classroom. Computers & Education, 194, 104684. doi:10.1016/j.compedu.2022.104684.

Vezne, R., Yildiz Durak, H., & Atman Uslu, N. (2023). Online learning in higher education: Examining the predictors of students’ online engagement. Education and Information Technologies, 28(2), 1865–1889. doi:10.1007/s10639-022-11171-9.

Cheng, Y. M. (2023). How Different Categories of Gamified Stimuli Affect Massive Open Online Courses Continuance Intention and Learning Performance? Mediating Roles of Internal Experiences. Social Science Computer Review, 41(2), 495–527. doi:10.1177/08944393221111928.

Kizilcec, R. F., & Halawa, S. (2015). Attrition and Achievement Gaps in Online Learning. Proceedings of the Second (2015) ACM Conference on Learning @ Scale. doi:10.1145/2724660.2724680.

Milligan, C., & Littlejohn, A. (2017). Why study on a MOOC? The motives of students and professionals. International Review of Research in Open and Distributed Learning, 18(2), 92–102. doi:10.19173/irrodl.v18i2.3033.

Veletsianos, G., Reich, J., & Pasquini, L. A. (2016). The Life Between Big Data Log Events. AERA Open, 2(3), 233285841665700. doi:10.1177/2332858416657002

Piccoli, G., Ahmad, R., & Ives, B. (2001). Web-Based Virtual Learning Environments: A Research Framework and a Preliminary Assessment of Effectiveness in Basic IT Skills Training. MIS Quarterly, 25(4), 401. doi:10.2307/3250989.

Altınpulluk, H., & Kesim, M. (2015). Paradigm Shifts in Augmented Reality Applications from Past to Present, Academic Informatics Conference: 4-6 February 2015. Anadolu University Eskişehir, Eskisehir, Türkiye.

Ng, J. Y. Y., Ntoumanis, N., Thøgersen-Ntoumani, C., Deci, E. L., Ryan, R. M., Duda, J. L., & Williams, G. C. (2012). Self-Determination Theory Applied to Health Contexts. Perspectives on Psychological Science, 7(4), 325–340. doi:10.1177/1745691612447309.

Lung-Guang, N. (2019). Decision-making determinants of students participating in MOOCs: Merging the theory of planned behavior and self-regulated learning model. Computers & Education, 134, 50–62. doi:10.1016/j.compedu.2019.02.004.

Hsu, L. (2022). EFL learners’ self-determination and acceptance of LMOOCs: the UTAUT model. Computer Assisted Language Learning, 36(7), 1177–1205. doi:10.1080/09588221.2021.1976210.

Arsovic, B., & Stefanovic, N. (2020). E-learning based on the adaptive learning model: case study in Serbia. Sādhanā, 45(1), 266. doi:10.1007/s12046-020-01499-8.

Stanley, T. (2021). What Is Authentic Learning? Authentic Learning, 7–15, Routledge, Oxfordshire, United Kingdom. doi:10.4324/9781003233152-2.

Kim, J.-H. (2021). The Effects of Problem Solving Ability, Collaborative Self-efficiency, ARCS Learning Motivation, and Learning Outcomes in e-PBL. Korean Association For Learner-Centered Curriculum And Instruction, 21(11), 137–156. doi:10.22251/jlcci.2021.21.11.137.

Velander, J., Otero, N., Pargman, T. C., & Milrad, M. (2021). “We Know What You Were Doing”. Visualizations and Dashboards for Learning Analytics. Advances in Analytics for Learning and Teaching. Springer, Cham, Switzerland. doi:10.1007/978-3-030-81222-5_15.

Haas, M. R. C., Haley, K., Nagappan, B. S., Ankel, F., Swaminathan, A., & Santen, S. A. (2020). The connected educator: personal learning networks. Clinical Teacher, 17(4), 373–377. doi:10.1111/tct.13146.

Oddone, K. (2022). The nature of teachers’ professional learning through a personal learning network: Individual, social and digitally connected. Teaching and Teacher Education: Leadership and Professional Development, 1, 100001. doi:10.1016/j.tatelp.2022.100001.

Ekoç, A. (2022). No teacher is an island: technology-assisted personal learning network (PLN) among English language teachers in Turkey. Interactive Learning Environments, 30(7), 1183–1199. doi:10.1080/10494820.2020.1712428.

Salinas, J., & De-Benito, B. (2020). Construction of personalized learning pathways through mixed methods. Comunicar, 28(65), 31–42. doi:10.3916/C65-2020-03.

Peng, H., Ma, S., & Spector, J. M. (2019). Personalized Adaptive Learning: An Emerging Pedagogical Approach Enabled by a Smart Learning Environment. Lecture Notes in Educational Technology, 171–176. doi:10.1007/978-981-13-6908-7_24.

Aldemir, T., Celik, B., & Kaplan, G. (2018). A qualitative investigation of student perceptions of game elements in a gamified course. Computers in Human Behavior, 78, 235–254. doi:10.1016/j.chb.2017.10.001.

Zakaria, A. (2024). A Systematic Review of Gamification in MOOCs: Effects on Student Motivation, Engagement, and Dropout Rates. Journal of Educators Online, 21(2). doi:10.9743/jeo.2024.21.2.15.

Yıldız, E. (2020). Investigation of Factors Affecting the Sense of Community of Distance Education Learners in Online Learning Environments. Journal of Qualitative Research in Education, 8(1), 180–205. doi:10.14689/issn.2148-2624.1.8c.1s.9m.

Celik, S. (2021). Power Distance and Teacher Authority in an Online Learning Environment. Research Anthology on Developing Effective Online Learning Courses, 1665–1680, IGI Global, Pennsylvania, United States. doi:10.4018/978-1-7998-8047-9.ch083.

Ginige, T. N. D. S., & Vanderwall, S. T. (2022). Effective online learning management system to improve and enhance the online learning and student engagement experience. 2022 the 6th International Conference on Information System and Data Mining. doi:10.1145/3546157.3546172.

Saravanan, K. (2018). MOOC for Student Learning and Active Engagement. Advances in Educational Technologies and Instructional Design, 127–146, IGI Global, Pennsylvania, United States. doi:10.4018/978-1-5225-3634-5.ch006.

Ranieri, M., Luzzi, D., Cuomo, S., & Bruni, I. (2022). If and how do 360° videos fit into education settings? Results from a scoping review of empirical research. Journal of Computer Assisted Learning, 38(5), 1199–1219. doi:10.1111/jcal.12683.

Intan Kurniasih, D., Baedhowi, & Sudiyanto. (2021). The Effectiveness of Higher Order Thinking Skills (HOTS) Based E-Book to Improve Student Learning Outcomes. ICLIQE 2021: Proceeding of The 5th International Conference on Learning Innovation and Quality Education. doi:10.1145/3516875.3516882.

Annan, D. K., Onodipe, D. G., & Stephenson, D. A. (2019). Using Student-Created Content Videos in Flipped Learning to Enhance Student Higher-Order Thinking Skills, Engagement, and Satisfaction. Journal of Education & Social Policy, 6(3), 1-4. doi:10.30845/jesp.v6n3p4.

McMillan, J. H. (2017). Using Students’ Assessment Mistakes and Learning Deficits to Enhance Motivation and Learning, Taylor & Francis Group, New York. doi:10.4324/9781315650890.

Vygotsky, L. S., & Cole, M. (1978). Mind in society: Development of higher psychological processes. Harvard University Press, Cambridge, United States.

Gozza-Cohen, M. (2015). Session 8: Accessible World | Practicing what we preach: Using Universal Design for Learning (UDL) Principles to Teach UDL to Pre-Service Special Education Teachers. WCSNE 2015 Proceedings. doi:10.20533/wcsne.2015.0038.

Peters, V. (2018). Meeting Learners Where They Are: Using Microsoft Forms to Drive Improvement in Learning Outcomes. Digital Promise. doi:10.51388/20.500.12265/52.

de Oliveira, L. C. (2023). A Language-Based Approach to Content Instruction (LACI) for Multilingual Learners. Supporting Multilingual Learners’ Academic Language Development, 1–12, Routledge, Oxfordshire, United Kingdom. doi:10.4324/9781003264927-1.

Mohd Sharif, M. S. A., & Ramakrisnan, P. (2023). Log Data Indicators for Identifying Learner Engagement in MOOCs. International Journal of Advanced Research in Education and Society, 5(1), 35–51. doi:10.55057/ijares.2023.5.1.5.

Masrom, U. K., Nik Mohd Alwi, N. A., & Nor Asshidin, N. H. (2018). The underlying factors of learner readiness and satisfaction in blended learning environment. 2018 IEEE 6th International Conference on MOOCs, Innovation and Technology in Education (MITE). doi:10.1109/mite.2018.8747109.

Hébert, T. P. (2021). Sofia Creates a Supportive Classroom Environment. Guiding Gifted Students With Engaging Books, 13–20, Routledge, Oxfordshire, United Kingdom. doi:10.4324/9781003235408-2.

Perifanou, M., & Economides, A. A. (2022). The Landscape of MOOC Platforms Worldwide. International Review of Research in Open and Distributed Learning, 23(3), 104–133. doi:10.19173/irrodl.v23i3.6294.

Chauhan, J., Taneja, S., & Goel, A. (2015). Enhancing MOOC with Augmented Reality, Adaptive Learning and Gamification. 2015 IEEE 3rd International Conference on MOOCs, Innovation and Technology in Education (MITE), Amritsar, India. doi:10.1109/mite.2015.7375343.

Schwenkreis, F. (2018). Coaching Support by Collecting and Analyzing Data (CoCoAnDa). Opportunities And Challenges for European Projects. doi:10.5220/0008862902200225.

Prediger, S. (2022). Implementation research as a task for subject-matter education disciplines: Co-constructive, content-related, and research-based. Research in Subject-Matter Teaching and Learning (RISTAL), 5(1), 4–23. doi:10.2478/ristal-2022-0103.

AlOkaily, R. (2023). Evaluations of Learning Designs. Learner-Centered Instructional Design and Evaluation, 49–112, Routledge, Oxfordshire, United Kingdom. doi:10.4324/9781003317234-5.

Amigud, A. (2019). Post-Traditional Learning Analytics. Emerging Trends in Learning Analytics, 13–25, Brill, Leiden, Netherlands. doi:10.1163/9789004399273_002.

Shaban, A., & Pearson, E. (2019). A Learning Design Framework to Support Children with Learning Disabilities Incorporating Gamification Techniques. Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems. doi:10.1145/3290607.3312806.

Cheng, Y.-M. (2023). How gamification and social interaction stimulate MOOCs continuance intention via cognitive presence, teaching presence and social presence? Library Hi Tech, 41(6), 1781–1801. doi:10.1108/lht-03-2022-0160.

Bothe, M., & Meinel, C. (2020). When Do Learners Rewatch Videos in MOOCs? 2020 IEEE Learning With MOOCS (LWMOOCS), Antigua Guatemala, Guatemala. doi:10.1109/lwmoocs50143.2020.9234368.

Bastedo, K., & Swenson, N. (2019). General Accessibility Guidelines for Online Course Content Creation. Universal Access Through Inclusive Instructional Design, 208–217, Routledge, Oxfordshire, United Kingdom. doi:10.4324/9780429435515-26.

Edney, S., Ryan, J. C., Olds, T., Monroe, C., Fraysse, F., Vandelanotte, C., Plotnikoff, R., Curtis, R., & Maher, C. (2019). User engagement and attrition in an app-based physical activity intervention: Secondary analysis of a randomized controlled trial. Journal of Medical Internet Research, 21(11), 14645. doi:10.2196/14645.

Abou-Khalil, V., Helou, S., Khalifé, E., Chen, M. A., Majumdar, R., & Ogata, H. (2021). Emergency online learning in low-resource settings: Effective student engagement strategies. Education Sciences, 11(1), 1–18. doi:10.3390/educsci11010024.

Battye, A. (2022). Multi-Modal Communication. Navigating AAC, 49–52, Routledge, Oxfordshire, United Kingdom. doi:10.4324/9781003296850-12.

Changchit, C., & Bagchi, K. (2017). Privacy and Security Concerns with Healthcare Data and Social Media Usage. Journal of Information Privacy and Security, 13(2), 49–50. doi:10.1080/15536548.2017.1322413.

Kong, A. (2022). Understanding MOOC Learners from Different Levels of Study: An Investigation of Hospitality and Tourism. 2022 IEEE Learning with MOOCS, Antigua Guatemala, Guatemala. doi:10.1109/lwmoocs53067.2022.9927928.


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DOI: 10.28991/ESJ-2024-SIED1-08

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