International Journal of Computer Science & Network Security

International Journal of Computer Science & Network Security (국제컴퓨터통신보호논문지학회)
권호 표지
DOI QR코드

DOI QR Code

A Critical Analysis of Learning Technologies and Informal Learning in Online Social Networks Using Learning Analytics

  • Received : 2024.01.05
  • Published : 2024.01.30
Download PDF
⟨ Previous Next ⟩

Abstract

This paper presents a critical analysis of the current application of big data in higher education and how Learning Analytics (LA), and Educational Data Mining (EDM) are helping to shape learning in higher education institutions that have applied the concepts successfully. An extensive literature review of Learning Analytics, Educational Data Mining, Learning Management Systems, Informal Learning and Online Social Networks are presented to understand their usage and trends in higher education pedagogy taking advantage of 21st century educational technologies and platforms. The roles of and benefits of these technologies in teaching and learning are critically examined. Imperatively, this study provides vital information for education stakeholders on the significance of establishing a teaching and learning agenda that takes advantage of today's educational relevant technologies to promote teaching and learning while also acknowledging the difficulties of 21st-century learning. Aside from the roles and benefits of these technologies, the review highlights major challenges and research needs apparent in the use and application of these technologies. It appears that there is lack of research understanding in the challenges and utilization of data effectively for learning analytics, despite the massive educational data generated by high institutions. Also due to the growing importance of LA, there appears to be a serious lack of academic research that explore the application and impact of LA in high institution, especially in the context of informal online social network learning. In addition, high institution managers seem not to understand the emerging trends of LA which could be useful in the running of higher education. Though LA is viewed as a complex and expensive technology that will culturally change the future of high institution, the question that comes to mind is whether the use of LA in relation to informal learning in online social network is really what is expected? A study to analyze and evaluate the elements that influence high usage of OSN is also needed in the African context. It is high time African Universities paid attention to the application and use of these technologies to create a simplified learning approach occasioned by the use of these technologies.

Keywords

References

  1. J. Furlong and C. Davies, 'Young people, new technologies and learning at home: Taking context seriously', Oxford Review of Education, vol. 38, no. 1, pp. 45-62, 2012. https://doi.org/10.1080/03054985.2011.577944
  2. D. Scearce, G. Kasper, and H. M. Grant, 'Working wikily', Standford Social Innovation Review, vol. 8, no. 3, pp. 30-37, 2010.
  3. T. H. Homan, Wolkenridders: over de binnenkant van organisatieverandering. Open Universiteit Nederland, 2006.
  4. L. Hamilton, What Facebook users share: Lower grandes. Time. 2009.
  5. M. De Laat and B. Schreurs, 'Visualizing informal professional development networks: Building a case for learning analytics in the workplace', American Behavioral Scientist, vol. 57, no. 10, pp. 1421-1438, 2013. https://doi.org/10.1177/0002764213479364
  6. D. Ifenthaler and J. Y.-K. Yau, 'Utilising learning analytics to support study success in higher education: a systematic review', Educational Technology Research and Development, vol. 68, no. 4, pp. 1961-1990, 2020. https://doi.org/10.1007/s11423-020-09788-z
  7. Y. Yang, Q. Wang, H. L. Woo, and C. L. Quek, 'Using Facebook for teaching and learning: a review of the literature', International Journal of Continuing Engineering Education and Life Long Learning, vol. 21, no. 1, pp. 72-86, 2011. https://doi.org/10.1504/IJCEELL.2011.039695
  8. P. Mahajan, 'Use of social networking in a linguistically and culturally rich India', The International Information & Library Review, vol. 41, no. 3, pp. 129-136, 2009. https://doi.org/10.1080/10572317.2009.10762807
  9. O. L. S. BUREAU, 'US department of Labor', College Enrollment and Work Activity of 2013 High School Graduates, 2007.
  10. E. B. Kozleski, D. Gibson, and A. Hynds, 'Transforming complex educational systems: Grounding systems issues in equity and social justice', Defining social justice leadership in a global context, pp. 263-286, 2012.
  11. R. Hammad and D. Ludlow, 'Towards a smart learning environment for smart city governance', in Proceedings of the 9th international conference on utility and cloud computing, 2016, pp. 185-190.
  12. R. S. Baker and K. Yacef, 'The state of educational data mining in 2009: A review and future visions', Journal of educational data mining, vol. 1, no. 1, pp. 3-17, 2009.
  13. J. A. Reyes, 'The skinny on big data in education: Learning analytics simplified', TechTrends, vol. 59, no. 2, pp. 75-80, 2015. https://doi.org/10.1007/s11528-015-0842-1
  14. D. Laurillard, 'The pedagogical challenges to collaborative technologies', International Journal of Computer-Supported Collaborative Learning, vol. 4, no. 1, pp. 5-20, 2009. https://doi.org/10.1007/s11412-008-9056-2
  15. K. Gibson, 'The moral basis of stakeholder theory', Journal of business ethics, pp. 245-257, 2000.
  16. R. L. Cross, R. L. Cross, and A. Parker, The hidden power of social networks: Understanding how work really gets done in organizations. Harvard Business Press, 2004.
  17. C. Thille, E. Schneider, R. F. Kizilcec, C. Piech, S. A. Halawa, and D. K. Greene, The future of data-enriched assessment. Research & Practice in Assessment, 9 (2), 5-16. 2014.
  18. A. G. Picciano, 'The evolution of big data and learning analytics in American higher education.', Journal of asynchronous learning networks, vol. 16, no. 3, pp. 9-20, 2012.
  19. J. Wellings and M. H. Levine, 'The digital promise: Transforming learning with innovative uses of technology', 2009.
  20. L. Johnson, S. Adams, and M. Cummins, Technology outlook for Australian tertiary education 2012-2017: An NMC Horizon Report regional analysis. The New Media Consortium, 2012.
  21. J. Dron and T. Anderson, Teaching crowds: Learning and social media. Athabasca University Press, 2014.
  22. S. Sergis and D. G. Sampson, 'Teaching and learning analytics to support teacher inquiry: A systematic literature review', Learning analytics: Fundaments, applications, and trends, pp. 25-63, 2017.
  23. D. Ifenthaler and C. Schumacher, 'Student perceptions of privacy principles for learning analytics', Educational Technology Research and Development, vol. 64, no. 5, pp. 923-938, 2016.
  24. C. Haythornthwaite, 'Strong, weak, and latent ties and the impact of new media', The information society, vol. 18, no. 5, pp. 385-401, 2002. https://doi.org/10.1080/01972240290108195
  25. H. Roreger and T. C. Schmidt, 'Socialize online learning: Why we should integrate learning content management with Online Social Networks', in 2012 IEEE International Conference on Pervasive Computing and Communications Workshops, 2012, pp. 685-690.
  26. J. Bruggeman, Social networks: An introduction. Routledge, 2013.
  27. C. Haythornthwaite and M. De Laat, 'Social networks and learning networks: Using social network perspectives to understand social learning', in Proceedings of the 7th international conference on networked learning, 2010, pp. 183-190.
  28. J. Williams, 'Social networking applications in health care: threats to the privacy and security of health information', in Proceedings of the 2010 ICSE workshop on software engineering in health care, 2010, pp. 39-49.
  29. D. M. Boyd and N. B. Ellison, 'Social network sites: Definition, history, and scholarship', Journal of computer-mediated Communication, vol. 13, no. 1, pp. 210-230, 2007.
  30. H. Tankovska, Social media-Statistics & Facts. Statista.Com. https://www.statista.com/topics/1164/social-networks, 2021. Last Accessed 2021/09/15
  31. S. B. Shum and R. Ferguson, 'Social learning analytics', Journal of educational technology & society, vol. 15, no. 3, pp. 3-26, 2012.
  32. S. Dawson, O. Poquet, C. Colvin, T. Rogers, A. Pardo, and D. Gasevic, 'Rethinking learning analytics adoption through complexity leadership theory', in Proceedings of the 8th international conference on learning analytics and knowledge, 2018, pp. 236-244.
  33. D. W. Livingstone, 'Researching expanded notions of learning and work and underemployment: Findings of the first Canadian survey of informal learning practices', International Review of Education, vol. 46, no. 6, pp. 491-514, 2000. https://doi.org/10.1023/A:1026522810394
  34. J. Osborne and J. Dillon, Research on learning in informal contexts: Advancing the field? Taylor & Francis, 2007.
  35. M. Rost, L. Barkhuus, H. Cramer, and B. Brown, 'Representation and communication: Challenges in interpreting large social media datasets', in Proceedings of the 2013 conference on Computer supported cooperative work, 2013, pp. 357-362.
  36. F. A. Hrabowski III and J. Suess, 'Reclaiming the lead: higher education's future and implications for technology', UMBC Office of the Vice President of Information Technology, 2010.
  37. D. Boud and P. Hager, 'Re-thinking continuing professional development through changing metaphors and location in professional practices', Studies in continuing education, vol. 34, no. 1, pp. 17-30, 2012. https://doi.org/10.1080/0158037X.2011.608656
  38. E. Lazega, 'Rationalite, discipline sociale et structure', Revue francaise de sociologie, vol. 44, no. 2, pp. 305-329, 2003.
  39. M. Patten, Questionnaire research: A practical guide. Routledge, 2016.
  40. M. Scheffel, H. Drachsler, S. Stoyanov, and M. Specht, 'Quality indicators for learning analytics', Journal of Educational Technology & Society, vol. 17, no. 4, pp. 117-132, 2014.
  41. J. Clarke and K. Nelson, 'Perspectives on learning analytics: issues and challenges. Observations from Shane Dawson and Phil Long', The International Journal of the First Year in Higher Education, vol. 4, no. 1, pp. 1-8, 2013.
  42. N. Dabbagh and A. Kitsantas, 'Personal Learning Environments, social media, and self-regulated learning: A natural formula for connecting formal and informal learning', The Internet and higher education, vol. 15, no. 1, pp. 3-8, 2012. https://doi.org/10.1016/j.iheduc.2011.06.002
  43. G. Siemens and P. Long, 'Penetrating the fog: Analytics in learning and education.', EDUCAUSE review, vol. 46, no. 5, p. 30, 2011.
  44. L. P. Macfadyen, 'Overcoming barriers to educational analytics: How systems thinking and pragmatism can help', Educational Technology, pp. 31-39, 2017.
  45. M. De Laat, V. Lally, L. Lipponen, and R.-J. Simons, 'Online teaching in networked learning communities: A multi-method approach to studying the role of the teacher', Instructional Science, vol. 35, no. 3, pp. 257-286, 2007.
  46. G. Veletsianos and C. Navarrete, 'Online social networks as formal learning environments: Learner experiences and activities', The International Review of Research in Open and Distributed Learning, vol. 13, no. 1, pp. 144-166, 2012. https://doi.org/10.19173/irrodl.v13i1.1078
  47. L. M. Miller and D. D. Prior, 'Online social networks and friending behaviour: A self-determination theory perspective', in Proceedings of the Australia and New Zealand Marketing Academy Annual Conference, Christchurch, New Zealand, 2010, pp. 1-9.
  48. C. Steinfield, N. B. Ellison, C. Lampe, and J. Vitak, 'Online social network sites and the concept of social capital', in Frontiers in new media research, Routledge, 2013, pp. 122-138.
  49. M. Warschauer and T. Matuchniak, 'New technology and digital worlds: Analyzing evidence of equity in access, use, and outcomes', Review of research in education, vol. 34, no. 1, pp. 179-225, 2010. https://doi.org/10.3102/0091732X09349791
  50. M. De Laat, 'Networked learning', 2006.
  51. S. P. Borgatti, A. Mehra, D. J. Brass, and G. Labianca, 'Network analysis in the social sciences', science, vol. 323, no. 5916, pp. 892-895, 2009. https://doi.org/10.1126/science.1165821
  52. P. Blikstein and M. Worsley, 'Multimodal learning analytics and education data mining: Using computational technologies to measure complex learning tasks', Journal of Learning Analytics, vol. 3, no. 2, pp. 220-238, 2016. https://doi.org/10.18608/jla.2016.32.11
  53. S. Cetintas, L. Si, H. P. Aagard, K. Bowen, and M. Cordova-Sanchez, 'Microblogging in a classroom: Classifying students' relevant and irrelevant questions in a microblogging-supported classroom', IEEE Transactions on Learning Technologies, vol. 4, no. 4, pp. 292-300, 2011. https://doi.org/10.1109/TLT.2011.14
  54. A. Karpinski, 'Media sensationalization of social science research: Social networking insites', Teachers College Record, 2009.
  55. L. Naismith, P. Lonsdale, G. Vavoula, and M. Sharples, 'Literature Review in Mobile. 5', RESULTADOS Technologies and Learning, 2004.
  56. J. Sefton-Green, 'Literature review in informal learning with technology outside school', 2004.
  57. C. Greenhow, B. Robelia, and J. E. Hughes, 'Learning, teaching, and scholarship in a digital age: Web 2.0 and classroom research: What path should we take now?', Educational researcher, vol. 38, no. 4, pp. 246-259, 2009. https://doi.org/10.3102/0013189X09336671
  58. A. Merceron, P. Blikstein, and G. Siemens, 'Learning analytics: From big data to meaningful data', Journal of Learning Analytics, vol. 2, no. 3, pp. 4-8, 2015.
  59. N. Sclater, A. Peasgood, and J. Mullan, Learning analytics in higher education: A review of UK and international practice Full report, Educause 39 (2016).
  60. Z. K. Papamitsiou and A. A. Economides, 'Learning analytics and educational data mining in practice: A systematic literature review of empirical evidence.', J. Educ. Technol. Soc., vol. 17, no. 4, pp. 49-64, 2014.
  61. G. Cormode and B. Krishnamurthy, 'Key differences between Web 1.0 and Web 2.0', First Monday, 2008.
  62. N. Carr, 'Is Google making us stupid: What the Internet is doing to our brains', 2008.
  63. S. Sergis, D. G. Sampson, and L. Pelliccione, 'Investigating the impact of Flipped Classroom on students' learning experiences: A Self-Determination Theory approach', Computers in Human Behavior, vol. 78, pp. 368-378, 2018.
  64. B. Barron, 'Interest and self-sustained learning as catalysts of development: A learning ecology perspective', Human development, vol. 49, no. 4, pp. 193-224, 2006.
  65. D. Ifenthaler, D. Gibson, and E. Dobozy, 'Informing learning design through analytics: Applying network graph analysis', Australasian Journal of Educational Technology, vol. 34, no. 2, 2018.
  66. C. Greenhow and B. Robelia, 'Informal learning and identity formation in online social networks', Learning, media and technology, vol. 34, no. 2, pp. 119-140, 2009. https://doi.org/10.1080/17439880902923580
  67. M. Callanan, C. Cervantes, and M. Loomis, 'Informal learning', Wiley Interdisciplinary Reviews: Cognitive Science, vol. 2, no. 6, pp. 646-655, 2011. https://doi.org/10.1002/wcs.143
  68. S. Kerka, 'Incidental Learning. Trends and Issues Alert No. 18.', 2000.
  69. N. Kvartalnyi, Impact of big data on education: history, benefits and examples. 2020.
  70. K.-W. Lai, 'ICT supporting the learning process: The premise, reality, and promise', in International handbook of information technology in primary and secondary education, Springer, 2008, pp. 215-230.
  71. G. Siemens, 'How data and analytics can improve education, July 2011', Retrieved on August, vol. 8, 2011.
  72. C. Greenhow and L. Burton, 'Help from my "friends": Social capital in the social network sites of low-income students', Journal of Educational Computing Research, vol. 45, no. 2, pp. 223-245, 2011. https://doi.org/10.2190/EC.45.2.f
  73. V. J. Rideout, U. G. Foehr, and D. F. Roberts, 'Generation m 2: Media in the lives of 8-to 18-year-olds.', Henry J. Kaiser Family Foundation, 2010.
  74. B. Czerkawski and J. N. Hernandez, 'Formal, non-formal, and informal e-learning experiences with emerging technologies: a case study of a Graduate Educational Technology Program', in Cases on formal and informal e-learning environments: Opportunities and practices, IGI Global, 2013, pp. 337-355.
  75. S. Kilis, Y. Gulbahar, and C. Rapp, 'Exploration of teaching preferences of instructors' use of social media', European Journal of Open, Distance and E-learning, vol. 19, no. 1, 2016.
  76. M. Bienkowski, M. Feng, and B. Means, 'Enhancing Teaching and Learning through Educational Data Mining and Learning Analytics: An Issue Brief.', Office of Educational Technology, US Department of Education, 2012.
  77. C. J. Atman et al., 'Enabling engineering student success: The final report for the Center for the Advancement of Engineering Education', San Rafael, CA: Morgan & Claypool Publishers, 2010.
  78. L. C. Giles, G. F. Glonek, M. A. Luszcz, and G. R. Andrews, 'Effect of social networks on 10 year survival in very old Australians: the Australian longitudinal study of aging', Journal of Epidemiology & Community Health, vol. 59, no. 7, pp. 574-579, 2005. https://doi.org/10.1136/jech.2004.025429
  79. P. J. Piety, D. T. Hickey, and M. J. Bishop, 'Educational data sciences: Framing emergent practices for analytics of learning, organizations, and systems', in Proceedings of the fourth international conference on learning analytics and knowledge, 2014, pp. 193-202.
  80. B. Bakhshinategh, O. R. Zaiane, S. ElAtia, and D. Ipperciel, 'Educational data mining applications and tasks: A survey of the last 10 years', Education and Information Technologies, vol. 23, no. 1, pp. 537-553, 2018. https://doi.org/10.1007/s10639-017-9616-z
  81. C. Romero and S. Ventura, 'Educational data mining and learning analytics: An updated survey', Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, vol. 10, no. 3, p. e1355, 2020.
  82. R. Zhou, 'Education web information retrieval and classification with big data analysis', Creative Education, vol. 7, no. 18, p. 2868, 2016.
  83. D. A. Erlandson, E. L. Harris, B. L. Skipper, and S. D. Allen, Doing naturalistic inquiry: A guide to methods. Sage, 1993.
  84. R. F. Kizilcec and C. Brooks, 'Diverse big data and randomized field experiments in massive open online courses: Opportunities for advancing learning research', G. siemens & c. lang (eds.), handbook on learning analytics & educational data mining, 2017.
  85. K.-W. Lai, 'Digital technology and the culture of teaching and learning in higher education', Australasian Journal of Educational Technology, vol. 27, no. 8, 2011.
  86. D. Ifenthaler, Designing effective digital learning environments: toward learning analytics design. Springer, 2017.
  87. R. centre Domo, 'Data Never Sleeps 9.0', Domo, 2021. https://www.domo.com/learn/infographic/data-never-sleeps-9 (accessed Oct. 19, 2021).
  88. K. J. Cios, W. Pedrycz, R. W. Swiniarski, and L. A. Kurgan, Data mining: a knowledge discovery approach. Springer Science & Business Media, 2007.
  89. E. Wagner and P. Ice, 'Data changes everything: Delivering on the promise of learning analytics in higher education.', Educause Review, vol. 47, no. 4, p. 32, 2012.
  90. S. Dawson, D. Gasevic, G. Siemens, and S. Joksimovic, 'Current state and future trends: A citation network analysis of the learning analytics field', in Proceedings of the fourth international conference on learning analytics and knowledge, 2014, pp. 231-240.
  91. D. R. Garrison, T. Anderson, and W. Archer, 'Critical thinking, cognitive presence, and computer conferencing in distance education', American Journal of distance education, vol. 15, no. 1, pp. 7-23, 2001.
  92. J. Han, M. Kamber, and D. Mining, 'Concepts and techniques', Morgan Kaufmann, vol. 340, pp. 94104-3205, 2006.
  93. C. Shirky, Cognitive surplus: Creativity and generosity in a connected age. Penguin UK, 2010.
  94. R. Besbes and S. Besbes, 'Cognitive dashboard for teachers professional development', in Qatar Foundation Annual Research Conference Proceedings Volume 2016 Issue 1, 2016, vol. 2016, no. 1, p. ICTPP2984.
  95. J. Voogt, O. Erstad, C. Dede, and P. Mishra, 'Challenges to learning and schooling in the digital networked world of the 21st century', Journal of computer assisted learning, vol. 29, no. 5, pp. 403-413, 2013. https://doi.org/10.1111/jcal.12029
  96. H. Chen, R. H. Chiang, and V. C. Storey, 'Business intelligence and analytics: From big data to big impact', MIS quarterly, pp. 1165-1188, 2012.
  97. A. Hofstein and S. Rosenfeld, 'Bridging the gap between formal and informal science learning', 1996.
  98. H. Eshach, 'Bridging in-school and out-of-school learning: Formal, non-formal, and informal education', Journal of science education and technology, vol. 16, no. 2, pp. 171-190, 2007.
  99. F. A. Hrabowski III, Boosting minorities in science. American Association for the Advancement of Science, 2011.
  100. K.-W. Lai, F. Khaddage, and G. Knezek, 'Blending student technology experiences in formal and informal learning', Journal of computer assisted learning, vol. 29, no. 5, pp. 414-425, 2013. https://doi.org/10.1111/jcal.12030
  101. A. McAfee, E. Brynjolfsson, T. H. Davenport, D. J. Patil, and D. Barton, 'Big data: the management revolution', Harvard business review, vol. 90, no. 10, pp. 60-68, 2012.
  102. N. Khan et al., 'Big data: survey, technologies, opportunities, and challenges', The scientific world journal, vol. 2014, 2014.
  103. M. Giacalone and S. Scippacercola, 'BIG DATA: ISSUES AND AN OVERVIEW IN SOME STRATEGIC SECTORS.', Journal of Applied Quantitative Methods, vol. 11, no. 3, 2016.
  104. B. K. Daniel, 'Big data in higher education: The big picture', in Big data and learning analytics in higher education, Springer, 2017, pp. 19-28.
  105. S. Erevelles, N. Fukawa, and L. Swayne, 'Big Data consumer analytics and the transformation of marketing', Journal of business research, vol. 69, no. 2, pp. 897-904, 2016.
  106. A. BAGHA and V. Madisetti, Big Data Analytics: A Hands-On Approach. USA: Arshdeep Bahga & Vijay Madisetti, 2019.
  107. A. IBM, 'Big data analytics', IBM, 2021. https://www.ibm.com/analytics/hadoop/big-data-analytics (accessed Oct. 19, 2021).
  108. W. Clark, K. Logan, R. Luckin, A. Mee, and M. Oliver, 'Beyond Web 2.0: Mapping the technology landscapes of young learners', Journal of computer assisted learning, vol. 25, no. 1, pp. 56-69, 2009. https://doi.org/10.1111/j.1365-2729.2008.00305.x
  109. D. Clow, 'An overview of learning analytics', Teaching in Higher Education, vol. 18, no. 6, pp. 683-695, 2013. https://doi.org/10.1080/13562517.2013.827653
  110. N. Rushby, 'An agenda for mobile learning.', British Journal of Educational Technology, vol. 43, no. 3, pp. 355-356, 2012. https://doi.org/10.1111/j.1467-8535.2012.01313.x
  111. M. Clark et al., 'Academic pathways study: Processes and realities', in 2008 Annual Conference & Exposition, 2008, p. 13.137. 1-13.137. 23.
  112. J. P. Campbell, P. B. DeBlois, and D. G. Oblinger, 'Academic analytics: A new tool for a new era', EDUCAUSE review, vol. 42, no. 4, p. 40, 2007.
  113. A. Nouira, L. Cheniti-Belcadhi, and R. Braham, 'An ontology- based framework of assessment analytics for massive learning', Computer Applications in Engineering Education, vol. 27, no. 6, pp. 1343-1360, 2019 https://doi.org/10.1002/cae.22155
  114. Z.-H. Zhou, 'Learnware: on the future of machine learning.', Frontiers Comput. Sci., vol. 10, no. 4, pp. 589-590, 2016. https://doi.org/10.1007/s11704-016-6906-3
  115. R. S. Burt, 'Network items and the general social survey', Social networks, vol. 6, no. 4, pp. 293-339, 1984.
  116. F. Henri, 'Computer conferencing and content analysis', in Collaborative learning through computer conferencing, Springer, 1992, pp. 117-136.
  117. A. I. Kiser and T. Porter, 'Social networking: Integrating students and university professor utilization', in Global Conference on Business and Finance Proceedings, 2011, vol. 6, no. 6, pp. 191-196.
  118. S. ElAtia and D. Ipperciel, 'Learning Analytics and Education Data Mining in Higher Education', in Advancing the Power of Learning Analytics and Big Data in Education, IGI Global, 2021, pp. 108-126.
  119. D. Lazer et al., 'Social science. Computational social science.', Science (New York, NY), vol. 323, no. 5915, pp. 721-723, 2009. https://doi.org/10.1126/science.1167742
  120. Okike, E. U., & Mogorosi, M. (n.d.). Educational Data Mining for Monitoring and Improving Academic Performance at University Levels. Environments, 4, 5.