Technology, Knowledge and Learning

, Volume 21, Issue 3, pp 285–305 | Cite as

Learning Analytics and Digital Badges: Potential Impact on Student Retention in Higher Education

Original research


Learning analytics and digital badges are emerging research fields in educational science. They both show promise for enhancing student retention in higher education, where withdrawals prior to degree completion remain at about 30 % in Organisation for Economic Cooperation and Development member countries. This integrative review provides an overview of the theoretical literature as well as current practices and experience with learning analytics and digital badges in higher education with regard to their potential impact on student retention to enhance students’ first-year experience. Learning analytics involves measuring and analyzing dynamic student data in order to gain insight into students’ learning processes and optimize learning and teaching. One purpose of learning analytics is to construct predictive models to identify students who risk failing a course and thus are more likely to drop out of higher education. Personalized feedback provides students with information about academic support services, helping them to improve their skills and therefore be successful in higher education. Digital badges are symbols for certifying knowledge, skills, and competencies on web-based platforms. The intention is to encourage student persistence by motivating them, recognizing their generic skills, signaling their achievements, and capturing their learning paths. This article proposes a model that synthesizes learning analytics, digital badges, and generic skills such as academic competencies. The main idea is that generic skills can be represented as digital badges, which can be used for learning analytics algorithms to predict student success and to provide students with personalized feedback for improvement. Moreover, this model may serve as a platform for discussion and further research on learning analytics and digital badges to increase student retention in higher education.


Learning analytics Digital badges Student retention Generic skills Academic competencies 


  1. Abramovich, S., Schunn, C., & Higashi, R. M. (2013). Are badges useful in education?: It depends upon the type of badge and expertise of learner. Educational Technology Research and Development, 61(2), 217–232. doi: 10.1007/s11423-013-9289-2.CrossRefGoogle Scholar
  2. ACT. (2008). College readiness standards. For EXPLORE, PLAN, and the ACT. Includes ideas for progress. Retrieved from
  3. Ahn, J., Pellicone, A., & Butler, B. S. (2014). Open badges for education: What are the implications at the intersection of open systems and badging? Research in Learning Technology, 22, 1–13.CrossRefGoogle Scholar
  4. Antin, J., & Churchill, E. F. (2011). Badges in social media: A social psychological perspective. Paper presented at the CHI Vancouver, Canada.Google Scholar
  5. Arnold, K. E. (2010). Signals: Applying academic analytics. EDUCAUSE Quarterly, 33, 1.Google Scholar
  6. Arnold, K. E., & Pistilli, M. D. (2012). Course signals at purdue: Using learning analytics to increase student success. In LAK ‘12 Proceedings of the 2nd international conference on learning analytics and knowledge. New York: ACM.Google Scholar
  7. Atkinson, J. W. (1957). Motivational determinants of risk-taking behavior. Psychological Review, 64(6), 359–372.CrossRefGoogle Scholar
  8. Bach, C. (2010). Learning analytics: Targeting instruction, curricula and student support. In Proceedings of the 4th international multi-conference on society, cybernetics and informatics. Orlando: International Institute of Informatics and Systematics.Google Scholar
  9. Baik, C., Naylor, R., & Arkoudis, S. (2015). The first year experience in Australian universities: Findings from two decades, 1994–2014. Melbourne: Melbourne Centre for the Study of Higher Education The University of Melbourne.Google Scholar
  10. Bandura, A., & Cervone, D. (1983). Self-evaluative and self-efficacy mechanisms governing the motivational effects of goal systems. Journal of Personality and Social Psychology, 45(5), 1017–1028.CrossRefGoogle Scholar
  11. Bandura, A., & Schunk, D. H. (1981). Cultivating competence, self-efficacy, and intrinsic interest through proximal self-motivation. Journal of Personality and Social Psychology, 41(3), 586–598.CrossRefGoogle Scholar
  12. Barber, R., & Sharkey, M. (2012). Course correction: Using analytics to predict course success. In LAK ‘12 Proceedings of the 2nd international conference on learning analytics and knowledge (pp. 259–262). New York: ACM.Google Scholar
  13. Barefoot, B. O., Warnock, C. L., Dickinson, M. P., Richardson, S. E., & Roberts, M. R. (Eds.). (1998). Exploring the evidence: Reporting outcomes of first-year seminars. (Vol. II). Columbia, SC: University of South Carolina, National Resource Center for the First-Year Experience and Students in Transition.Google Scholar
  14. Bean, J. P., & Metzner, B. S. (1985). A conceptual model of nontraditional undergraduate student attrition. Review of Educational Research, 55(4), 485–540.CrossRefGoogle Scholar
  15. Bennett, N., Dunne, E., & Carré, C. (1999). Patterns of core and generic skill provision in higher education. Higher Education, 37(1), 71–93. doi: 10.1023/A:1003451727126.CrossRefGoogle Scholar
  16. Berge, Z. L., & Muilenburg, L. Y. (2016). In the eye of the beholder: The value of digital badges. In L. Y. Muilenburg & Z. L. Berge (Eds.), Digital Badges in Education: Trends, Issues, and Cases (pp. 102–108). New York, London: Routledge.Google Scholar
  17. Binkley, M., Erstad, O., Herman, J., Raizen, S., Ripley, M., Miller-Ricci, M., & Rumble, M. (2012). Defining twenty-first century skills. In P. Griffin, B. McGaw, & E. Care (Eds.), Assessment and teaching of 21st century skills (pp. 17–66). Springer: New York.CrossRefGoogle Scholar
  18. Bowles, A., Fisher, R., McPhail, R., Rosenstreich, D., & Dobson, A. (2014). Staying the distance: Students´ perception of enablers of transition to higher education. Higher Education Research & Development, 33(2), 212–225.CrossRefGoogle Scholar
  19. Brinkworth, R., McCann, B., Matthews, C., & Nordström, K. (2009). First year expectations and experiences: Student and teacher perspectives. Higher Education, 58(2), 157–173.CrossRefGoogle Scholar
  20. Campbell, J. P., DeBlois, P. B., & Oblinger, D. G. (2007). Academic analytics: A new tool for a new era. EDUCAUSE Review, 42(4), 40–57.Google Scholar
  21. Campbell, J. P., & Oblinger, D. G. (2007). Academic analytics. Retrieved from
  22. Chatti, M., Dyckhoff, A. L., Schroeder, U., & Thüs, H. (2012). A reference model for learning analytics. International Journal of Technology Enhanced Learning, 4(5–6), 318–331.CrossRefGoogle Scholar
  23. Clanchy, J., & Ballard, B. (1995). Generic Skills in the Context of Higher Education. Higher Education Research & Development, 14(2), 155–166. doi: 10.1080/0729436950140202.CrossRefGoogle Scholar
  24. Clark, M. H., & Cundiff, N. L. (2011). Assessing the effectiveness of a college freshman seminar using propensity score adjustments. Research in Higher Education, 52(6), 616–639. doi: 10.1007/s11162-010-9208-x.CrossRefGoogle Scholar
  25. Colvin, C., Rogers, T., Wade, A., Dawson, S., Gašević, D., Shum, S. B., & Fisher, J. (2015). Student retention and learning analytics: A snapshot of Australian practices and a framework for advancement. Australia: Department of Education.Google Scholar
  26. Conley, D. T. (2011). Defining and measuring college and career readiness. Retrieved from
  27. Cormier, D., & Siemens, G. (2010). The open course. Through the open door: Open courses as research, learning and engagement. EDUCAUSE Review, 45(4), 30–39.Google Scholar
  28. Corrin, L., & de Barba, P. (2014). Exploring students’ interpretation of feedback delivered through learning analytics dashboards. In B. Hegarty, J. McDonald & S.-K. Loke (Eds.), Rhetoric and reality: Critical perspectives on educational technology. Proceedings ascilite Dunedin 2014 (pp. 629–633). Dunedin, NZ.Google Scholar
  29. Corrin, L., Kennedy, G., & Mulder, R. (2013). Enhancing learning analytics by understanding the needs of teachers. In Proceedings electric dreams, 30th ascilite conference. Sydney, Australia.Google Scholar
  30. Crisp, G., Palmer, E., Turnbull, D., Nettelbeck, T., & Ward, L. (2009). First year student expectations: Results from a university-wide student survey. Journal od University Teaching & Learning Practice, 6(1), 13–26.Google Scholar
  31. Dahlstrom, E., Brooks, C., & Bichsel, J. (2014). The current ecosystem of learning management systems in higher education: Student, faculty, and IT perspectives. Louisville, CO: ECAR.Google Scholar
  32. de Freitas, S., Gibson, D., Du Plessis, C., Halloran, P., Williams, E., Ambrose, M., & Arnab, S. (2015). Foundations of dynamic learning analytics: Using university student data to increase retention. British Journal of Educational Technology, 46(6), 1175–1188. doi: 10.1111/bjet.12212.CrossRefGoogle Scholar
  33. Deci, E. L. (1971). Effects of externally mediated rewards of instrinsic motivation. Journal of Personality and Social Psychology, 18(1), 105–115.CrossRefGoogle Scholar
  34. Deci, E. L., Vallerand, R. J., Pelletier, L. G., & Ryan, R. M. (1991). Motivation and education: The self-determination perspective. Educational Psychologist, 26(3–4), 325–346.CrossRefGoogle Scholar
  35. Deterding, S., Dixon, D., Khaled, R., & Nacke, L. (2011). From game design elements to gamefulness: Defining “Gamification”. In MindTrek ‘11 Proceedings of the 15th international academic MindTrek conference: Envisioning future media environments, September 2830, 2011 (pp. 9–15). New York: ACM New York.Google Scholar
  36. Dimitrijević, S., Devedzić, V., Jovanović, J., & Milikić, N. (2016). Badging platforms: A scenario-based comparison features and uses. In D. Ifenthaler, N. Bellin-Mularski, & D.-K. Mah (Eds.), Foundations of digital badges and micro-credentials: Demonstrating and recognizing knowledge and competencies. New York: Springer.Google Scholar
  37. Dona, K. L., Gregory, J., Salmon, G., & Pechenkina, E. (2014). Badges in the carpe diem MOOC. Paper presented at the ascilite conference, Dunedin, New Zealand.Google Scholar
  38. Drachsler, H., & Greller, W. (2016). Privacy and analytics: it’s a DELICATE issue: A checklist for trusted learning analytics. In LAK ‘16 Proceedings of the sixth international conference on learning analytics & knowledge (pp. 89–98). New York: ACM.Google Scholar
  39. EDUCAUSE (2012). 7 things you should know about badges. Retrieved March 8, 2016, from
  40. Elkordy, A. (2016). Development and implementation of digital badges for learning stem practices in secondary contexts: A pedagogical approach with empirical evidence. In D. Ifenthaler, N. Bellin-Mularski, & D.-K. Mah (Eds.), Foundations of digital badges and micro-credentials: Demonstrating and recognizing knowledge and competencies. New York: Springer.Google Scholar
  41. European Commission (2014). The GRASS project. Retrieved May, 24, 2016, from
  42. Evans, M. (2000). Planning for the transition to tertiary study: A literature review. Australasian Association for Institutional Research Journal, 9(1), 1–13.Google Scholar
  43. Ferguson, R. (2012). Learning analytics: drivers, developments and challenges. International Journal of Technology Enhanced Learning, 4(5/6), 304–317.CrossRefGoogle Scholar
  44. Ferguson, R., Hoel, T., Scheffel, M., & Drachsler, H. (2016). Guest editorial: Ethics and privacy in learning analytics. Journal of Learning Analytics, 3(1), 5–15.CrossRefGoogle Scholar
  45. Fiaidhi, J. (2014). The next step for learning analytics. IT Professional, 16(5), 4–8. doi: 10.1109/MITP.2014.78.CrossRefGoogle Scholar
  46. Finkelstein, J., Knight, E., & Manning, S. (2013). The potential and value of using digital badges for adult learners. Washington, DC: American Institutes for Research.Google Scholar
  47. Försterling, F. (2001). Attribution. An introduction to theories, research and applications. East Sussex, UK: Psychology Press Ltd.Google Scholar
  48. Foster, J. C. (2013). The promise of digital badges. Techniques: Connecting Education & Careers, 88(8), 31–34.Google Scholar
  49. Fournier, H., Kop, R., & Sitlia, H. (2011). The value of learning analytics to networked learning on a personal learning environment. In LAK ‘11 Proceedings of the 1st international conference on learning analytics and knowledge. New York: ACM.Google Scholar
  50. Gamrat, C., & Zimmerman, H. T. (2016). Teacher learning journeys: A design case study of a learners-centered STEM. In L. Y. Muilenburg & Z. L. Berge (Eds.), Digital badges in education. Trends, issues, and cases (pp. 215–225). New York: Routledge.Google Scholar
  51. Gašević, D., Dawson, S., & Jovanović, J. (2016). Ethics and privacy as enablers of learning analytics. Journal of Learning Analytics, 3(1), 1–4.CrossRefGoogle Scholar
  52. Gibson, D., & de Freitas, S. (2015). Exploratory analysis in learning analytics. Technology, Knowledge and Learning, 21(1), 5–19.CrossRefGoogle Scholar
  53. Gibson, D., Ostashewski, N., Flintoff, K., Grant, S., & Knight, E. (2013). Digital badges in education. Education and Information Technologies, 20(2), 403–410. doi: 10.1007/s10639-013-9291-7.CrossRefGoogle Scholar
  54. Glover, I. (2016). Student perceptions of digital badges as recognition of achievement and engagement in co-curricular activities. In D. Ifenthaler, N. Bellin-Mularski, & D.-K. Mah (Eds.), Foundations of digital badges and micro-credentials: Demonstrating and recognizing knowledge and competencies. New York: Springer.Google Scholar
  55. Glover, I., & Latif, F. (2013). Investigating perceptions and potential of open badges in formal higher education. In J. Herrington, A. Couros, & V. Irvine (Eds.), Proceedings of EdMedia: World conference on educational media and technology 2013 (pp. 398–1402). Victoria, Canada: Association for the Advancement of Computing in Education (AACE).Google Scholar
  56. Goldfinch, J., & Hughes, M. (2007). Skills, learning styles and success of first-year undergraduates. Active Learning in Higher Education, 8(3), 259–273. doi: 10.1177/1469787407081881.CrossRefGoogle Scholar
  57. Grant, S. (2014). What counts as learning: Open digital badges for new opportunities. Irvine, CA: Digital Media and Learning Research Hub.Google Scholar
  58. Greller, W., & Drachsler, H. (2012). Translating learning into numbers: A generic framework for learning analytics. Educational Technology & Society, 15(3), 42–57.Google Scholar
  59. Greller, W., Ebner, M., & Schön, M. (2014). Learning analytics: From theory to practice–data support for learning and teaching. In M. Kalz & E. Ras (Eds.), Computer assisted assessment research into E-Assessment (pp. 79–87). Switzerland: Springer International Publishing.Google Scholar
  60. Griffin, P., McGaw, B., & Care, E. (Eds.). (2012). Assessment and teaching of 21st century skills. New York: Springer.Google Scholar
  61. Halavais, A. M. C. (2012). A genealogy of badges. Information, Communication & Society, 15(3), 354–373.CrossRefGoogle Scholar
  62. Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112. doi: 10.3102/003465430298487.CrossRefGoogle Scholar
  63. Heckhausen, H., Schmalt, H.-D., & Schneider, K. (1985). Achievement motivation in perspective. Orlando, FL: Academic Press Inc.Google Scholar
  64. Heublein, U. (2014). Student drop-out from German higher education institutions. European Journal of Education, 49(4), 497–513.CrossRefGoogle Scholar
  65. Hickey, D. (2012). Intended purposes versus actual function of digital badges. Retrieved March 8, 2016, from
  66. Hickey, D. (2014). New project: Open badges in open edX and Beyond. Retrieved March 8, 2016, from
  67. Hughes, G., & Smail, O. (2015). Which aspects of university life are most and least helpful in the transition to HE? A qualitative snapshot of student perceptions. Journal of Further and Higher Education, 39(4), 466–480. doi: 10.1080/0309877X.2014.971109.CrossRefGoogle Scholar
  68. Ifenthaler, D. (2015). Learning analytics. In J. M. Spector (Ed.), The SAGE encyclopedia of educational technology (Vol. 2, pp. 447–451). Thousand Oaks, CA: Sage.Google Scholar
  69. Ifenthaler, D., Adcock, A. B., Erlandson, B. E., Gosper, M., Greiff, S., & Pirnay-Dummer, P. (2014). Challenges for education in a connected world: Digital learning, data rich environments, and computer-based assessment—Introduction to the inaugural special issue of technology, knowledge and learning. Technology, Knowledge and Learning, 19(1), 121–126.CrossRefGoogle Scholar
  70. Ifenthaler, D., Bellin-Mularski, N., & Mah, D.-K. (2016). Foundations of digital badges and micro-credentials: Demonstrating and recognizing knowledge and competencies. New York: Springer.CrossRefGoogle Scholar
  71. Ifenthaler, D., & Widanapathirana, C. (2014). Development and validation of a Learning Analytics framework: Two case studies using support vector machines. Technology, Knowledge and Learning, 19(1–2), 221–240.CrossRefGoogle Scholar
  72. Jackson, L. M., Pancer, S. M., Pratt, M. W., & Hunsberger, B. E. (2000). Great expectations: The relation between expectancies and adjustment during the transition to university. Journal of Applied Social Psychology, 30(10), 2100–2125.CrossRefGoogle Scholar
  73. Jansen, E. P. W. A., André, S., & Suhre, C. (2013). Readiness and expectations questionnaire: A cross-cultural measurement instrument for first-year university students. Educational Assessment, Evaluation and Accountability, 25(2), 115–130. doi: 10.1007/s11092-013-9161-2.CrossRefGoogle Scholar
  74. Jansen, E. P. W. A., & Suhre, C. (2011). Preparedness, first-year experiences and outcomes. A comparison between students in domestic and international degree programmes in a Dutch university. Paper presented at the Research and Development in Higher Education: Higher Eduation on the Edge Gold Coast, Australia.Google Scholar
  75. Jansen, E. P. W. A., & van der Meer, J. (2007). First-year students’ expectations and perceptions of readiness before they start university. Paper presented at the 30th annual HERDSA conference: Enhancing Higher Education: Theory and Scholarship, Adelaide.Google Scholar
  76. Jayaprakash, S. M., Moody, E. W., Lauría, E. J. M., & Baron, J. D. (2014). Early alert of academically at-risk students: An open source analytics initiative. Journal of Learning Analytics, 1(1), 6–47.Google Scholar
  77. Johnson, L., Adams Becker, S., Cummins, M., Estrada, V., Freeman, A., & Ludgate, H. (2013). NMC horizon report: 2013 higher education edition. Austin, Texas: The New Media Consortium.Google Scholar
  78. Johnson, L., Adams Becker, S., Estrada, V., & Freeman, A. (2014). NMC horizon report: 2014 higher education edition. Austin, Texas: The New Media Consortium.Google Scholar
  79. Jovanovic, J., & Devedžić, V. (2015). Open badges: Novel means to motivate, scaffold and recognize learning. Technology, Knowledge and Learning, 20(1), 115–122. doi: 10.1007/s10758-014-9232-6.CrossRefGoogle Scholar
  80. Kantanis, T. (2000). The role of social transition in students’ adjustment to the first-year of university. Journal of Institutional Research, 9(1), 100–110.Google Scholar
  81. Keller, J. M. (1987). Development and use of the ARCS Model of instructional design. Journal of Instructional Development, 10(3), 2–10.CrossRefGoogle Scholar
  82. Kelley, T., & Hickey, D. (2014). Major highlights of the 2013 educational assessment BOOC. Retrieved March 8, 2016, from
  83. Keup, J. R. (2005). The impact of curricular interventions on intended second year re-enrollment. Journal of college Student Retention, 7(1–2), 61–89.CrossRefGoogle Scholar
  84. Krause, K.-L. (2005). Serious thoughts about dropping out in first year: Trends, patterns and implications for higher education. Studies in Learning, Evaluation, Innovation and Development, 2(3), 55–68.Google Scholar
  85. Kuh, G., et al. (2005). Student success in college: Creating conditions that matter. San Francisco: Jossey-Bass.Google Scholar
  86. Lai, K.-W., & Hong, K.-S. (2014). Technology use and learning characteristics of students in higher education: Do generational differences exist? British Journal of Educational Technology, 46(4), 725–738. doi: 10.1111/bjet.12161.CrossRefGoogle Scholar
  87. Lauría, E. J. M., Baron, J. D., Devireddy, M., Sundararaju, V., & Jayaprakash, S. M. (2012). Mining academic data to improve college student retention: An open source perspective. In LAK ‘13 Proceedings of the 3rd international conference on learning analytics and knowledge (pp. 139–142). New York: ACM.Google Scholar
  88. Leggett, M., Kinnear, A., Boyce, M., & Bennett, I. (2004). Student and staff perceptions of the importance of generic skills in science. Higher Education Research & Development, 23(3), 295–312. doi: 10.1080/0729436042000235418.CrossRefGoogle Scholar
  89. Lepper, M. R., Greene, D., & Nisbett, R. E. (1973). Undermining children’s intrinsic interest with extrinsic reward: A test of the “overjustification” hypothesis. Journal of Personality and Social Psychology, 28(1), 129–137.CrossRefGoogle Scholar
  90. Long, P., & Siemens, G. (2011). Penetrating the fog: Analytics in learning and education. EDUCAUSE Review, 46(5), 31–40.Google Scholar
  91. Malone, T. W., & Lepper, M. R. (1987). Making learning fun: A taxonomy of intrinsic motivations for learning. In R. E. Snow & M. J. Farr (Eds.), Aptitude, learning and instruction III: Conative and affective process analyses (pp. 223–253). Hilsdale, NJ: Erlbaum.Google Scholar
  92. Margaryan, A., Littlejohn, A., & Vojt, G. (2011). Are digital natives a myth or reality? University students’ use of digital technologies. Computers & Education, 56(2), 429–440.CrossRefGoogle Scholar
  93. McDaniel, R., & Fanfarelli, J. (2016). Building better digital badges: Pairing completion logic with psychological factors. Simulation & Gaming, 47(1), 1–30.CrossRefGoogle Scholar
  94. Metzger, E. C., Lubin, L., Patten, R., & Whyte, J. (2016). Applied gamification: Creating reward systems for organizational professional development. In D. Ifenthaler, N. Bellin-Mularski, & D.-K. Mah (Eds.), Foundations of digital badges and micro-credentials: Demonstrating and recognizing knowledge and competencies. New York: Springer.Google Scholar
  95. Moon, M.-K., Jahng, S.-G., & Kim, T.-Y. (2011). A computer-assisted learning model based on the digital game exponential reward system. Turkish Online Journal of Educational Technology, 10(1), 1–14.Google Scholar
  96. Mozilla Foundation and Peer 2 Peer University (2012). Open badges for lifelong learning. Exploring an open badge ecosystem to support skill development and lifelong learning for real results such as jobs and advancement. Retrieved from
  97. Murray, M. C., & Pérez, J. (2014). Unraveling the digital literacy paradox: How higher education fails at the fourth literacy. Issues in Informing Science and Information Technology, 11, 85–100.Google Scholar
  98. Nadelson, L. S., Semmelroth, C., Martinez, G., Featherstone, M., Fuhriman, C. A., & Sell, A. (2013). Why did they come here? The influences and expectations of first-year students’ college experience. Higher Education Studies, 3(1), 50–62.CrossRefGoogle Scholar
  99. Newby, T., Wright, C., Besser, E., & Beese, E. (2016). Passport to creating and issuing digital instructional badges. In D. Ifenthaler, N. Bellin-Mularski, & D.-K. Mah (Eds.), Foundations of digital badges and micro-credentials: Demonstrating and recognizing knowledge and competencies. New York: Springer.Google Scholar
  100. OECD. (2013a). Education at a glance 2013: OECD indicators. Retrieved from
  101. OECD. (2013b). Skilled for life? Key findings from the survey of adult skills. Retrieved from
  102. OECD. (2014). PISA 2012 results in focus. What 15-year-old know and what they can do with what they know. Retrieved from
  103. Oliver, B. (2016). Better 21C Credentials. Evaluating the promise, perils and disruptive potential of digital credentials. Australia: Deakin University.Google Scholar
  104. Papamitsiou, Z., & Economides, A. (2014). Learning analytics and educational data mining in practice: A systematic literature review of empirical evidence. Educational Technology & Society, 17(4), 49–64.Google Scholar
  105. Pardo, A., & Siemens, G. (2014). Ethical and privacy principles for learning analytics. British Journal of Educational Technology, 45(3), 438–450.CrossRefGoogle Scholar
  106. Pistilli, M. D., & Arnold, K. E. (2010). In practice: Purdue signals: Mining real-time academic data to enhance student success. About Campus, 15(3), 22–24. doi: 10.1002/abc.20025.CrossRefGoogle Scholar
  107. Põldoja, H., & Laanpere, M. (2014). Exploring the potential of open badges in blog-based university courses. In Y. Cao, T. Väljataga, J. K. T. Tang, H. Leung, & M. Laanpere (Eds.), New horizons in web based learning (pp. 172–178). Switzerland: Springer.Google Scholar
  108. Prensky, M. (2001). Digital natives, digital immigrants. On the Horizon, 9(5), 1–6.CrossRefGoogle Scholar
  109. Prinsloo, P., & Slade, S. (2013). An evaluation of policy frameworks for addressing ethical considerations in learning analytics. In LAK ‘13 Proceedings of the 3rd international conference on learning analytics and knowledge. New York: ACM.Google Scholar
  110. Pursel, B. K., Stubbs, C., Woong Choi, G., & Tietjen, P. (2016). Digital badges, learning at scale, and big data. In L. Y. Muilenburg & Z. L. Berge (Eds.), Digital badges in education: Trends, issues, and cases (pp. 93–101). New York, London: Routledge.Google Scholar
  111. Randall, D. J., Harrison, J. B., & West, R. E. (2013). Giving credit where credit is due: Designing open badges for a technology integration course. TechTrends, 57(6), 88–95. doi: 10.1007/s11528-013-0706-5.CrossRefGoogle Scholar
  112. Reason, R. D., Terenzini, P. T., & Domingo, R. J. (2006). First things first: Developing academic competence in the first year of college. Research in Higher Education, 47(2), 149–175.CrossRefGoogle Scholar
  113. Resnick, M. (2012). Still a badge skeptic.
  114. Romero, C., Ventura, S., Espejo, P. G., & Hervás, C. (2008). Data mining algorithms to classify students. Paper presented at the 1st international conference on educational data mining, Montréal, Québec, Canada.Google Scholar
  115. Rovai, A. P. (2003). In search of higher persistence rates in distance education online programs. Internet und Higher Education, 6, 1–16.CrossRefGoogle Scholar
  116. Scheffel, M., Drachsler, H., & Specht, M. (2015). Developing an evaluation framework of quality indicators for learning analytics. In LAK ‘15 Proceedings of the 5th international conference on learning analytics and knowledge (pp. 16–20). New York: ACM.Google Scholar
  117. Scheffel, M., Drachsler, H., Stoyanov, S., & Specht, M. (2014). Quality indicators for learning analytics. Educational Technology & Society, 17(4), 117–132.Google Scholar
  118. Schulmeister, R. (2010). Students, internet, eLearning and web 2.0. In M. Ebner & M. Schiefner (Eds.), Looking toward the future of technology-enhanced education: Ubiquitous learning and digital native. Hershey, PA: IGI Global.Google Scholar
  119. Schuster, B., Försterling, F., & Weiner, B. (1989). Perceiving the causes of success and failure. A cross-cultural examination of attributional concepts. Journal of Cross-Cultural Psychology, 20(2), 191–213.CrossRefGoogle Scholar
  120. Sclater, N., & Bailey, P. (2015). Code of practice for learning analytics. Retrieved from
  121. Sclater, N., Peasgood, A., & Mullan, J. (2016). Learning analytics in higher education. A review of UK and international practice. Full report. Retrieved from https://
  122. Scott, G., Shah, M., Grebennikov, L., & Singh, H. (2008). Improving student retention: A university of Western Sydney case study. Journal of Institutional Research, 14(1), 9–23.Google Scholar
  123. Selwyn, N. (2009). The digital native-myth and reality. Aslib Proceedins: New Information Perspectives, 61(4), 364–379. doi: 10.1108/00012530910973776.CrossRefGoogle Scholar
  124. Shehata, S., & Arnold, K. E. (2015). Measuring student success using predictive engine. In LAK ‘15 Proceedings of the 5th international conference on learning analytics and knowledge. New York: ACM.Google Scholar
  125. Shum, S. B., & Crick, R. D. (2012). Learning dispositions and transferable competencies: Pedagogy, modelling and learning analytics. In LAK ‘12 Proceedings of the 2nd international conference on learning analytics and knowledge (pp. 92–101). New York: ACM.Google Scholar
  126. Siemens, G. (2012). Learning analytics: Envisioning a research discipline and a domain of practice. In LAK ‘12 Proceedings of the 2nd international conference on learning analytics and knowledge (pp. 4–8). New York: ACM.Google Scholar
  127. Siemens, G. (2013). Learning analytics: The emergence of a discipline. American Behavioral Scientist, 57(10), 1380–1400.CrossRefGoogle Scholar
  128. Siemens, G., Dawson, S., & Lynch, G. (2013). Improving the quality and productivity of the higher education sector. Policy and strategy for systems-level deployment of learning analytics. Retrieved from
  129. Siemens, G., Gašević, D., Haythornthwaite, C., Dawson, S., Buckingham Shum, S., Ferguson, R., Duval, E., Verbert, K., & Baker, R. S. J. d. (2011). Open learning analytics: An integrated & modularized platform. Proposal to design, implement and evaluate an open platform to integrate heterogeneous learning analytics techniques. Retrieved from
  130. Slade, S., & Galpin, F. (2012). Learning analytics and higher education: Ethical perspectives. In LAK ‘12 Proceedings of the 2nd international conference on learning analytics and knowledge (pp. 16–17). New York: ACM.Google Scholar
  131. Slade, S., & Prinsloo, P. (2013). Learning analytics: Ethical issues and dilemmas. American Behavioral Scientist, 57(10), 1509–1528.CrossRefGoogle Scholar
  132. Smith, J. S., & Wertlieb, E. C. (2005). Do first-year college students’ expectations align with their first-year experiences? NASPA Journal, 42(2), 153–174.CrossRefGoogle Scholar
  133. Sullivan, F. (2013). New and alternative assessments, digital badges and civics: An overview of emerging themes and promising directions (CIRCLE Working Paper No. 77). Medford, MA: Center for Information and Research on Civic Learning and Engagement.Google Scholar
  134. Tanes, Z., Arnold, K. E., Selzer King, A., & Remnet, M. A. (2011). Using signals for appropriate feedback: Perceptions and practices. Computers & Education, 57(4), 2414–2422.CrossRefGoogle Scholar
  135. Taylor, J. A., & Bedford, T. (2004). Staff perceptions of factors related to non-completion in higher education. Studies in Higher Education, 29(3), 375–394.CrossRefGoogle Scholar
  136. Thomas, L. (2002). Student retention in higher education: the role of institutional habitus. Journal of Education Policy, 17(4), 423–442. doi: 10.1080/02680930210140257.CrossRefGoogle Scholar
  137. Tinto, V. (1975). Dropout from higher education: A theoretical synthesis of recent research. Review of Educational Research, 45(1), 89–125. doi: 10.3102/00346543045001089.CrossRefGoogle Scholar
  138. Tinto, V. (1993). Leaving college. Rethinking the causes and cures of student attrition. Chicago; London: The University of Chicago Press.Google Scholar
  139. Tinto, V. (2012). Completing College, Rethinking Institutional Action. Chicago; London: The University of Chicago Press.CrossRefGoogle Scholar
  140. Tran, C., Schenke, K., & Hickey, D. T. (2014). Design principles for motivating learning with digital badges: Consideration of contextual factors of recognition and assessment. In ICLS 2014 Proceedings.Google Scholar
  141. Tremblay, K., Lalancette, D., & Roseveare, D. (2012). Assessment of higher education learning outcomes. In Feasibility study report. Design and implementation (Vol. 1). OECD.Google Scholar
  142. Verbert, K., Duval, E., Klerkx, J., Govaerts, S., & Santos, J. S. (2013). Learning analytics dashboard applications. American Behavioral Scientist, 57(10), 1500–1509.CrossRefGoogle Scholar
  143. Waters, D. (2003). Supporting first-year students in the bachelor of arts: An investigation of academic staff attitudes. Arts and Humanities in Higher Education, 2(3), 293–312. doi: 10.1177/14740222030023006.CrossRefGoogle Scholar
  144. Weiner, B. (1985). An attributional theory of achievement motivation and emotion. Psychological Review, 92(4), 548–573.CrossRefGoogle Scholar
  145. Weiner, B. (1986). An atrributional theory of motivation and emotion. New York: Springer.CrossRefGoogle Scholar
  146. Weinstein, C. E., & Palmer, D. R. (1990). LASSI-HS user’s manual. Clearwater, Florida: H&H Publishing Company.Google Scholar
  147. West, D., & Lockley, A. (2016). Implementing digital badges: The importance of institutional context. In D. Ifenthaler, N. Bellin-Mularski, & D.-K. Mah (Eds.), Foundations of digital badges and micro-credentials: Demonstrating and recognizing knowledge and competencies. New York: Springer.Google Scholar
  148. Willcoxson, L., Cotter, J., & Joy, S. (2011). Beyond the first-year experience: The impact on attrition of student experiences throughout undergraduate degree studies in six diverse universities. Studies in Higher Education, 36(3), 331–352.CrossRefGoogle Scholar
  149. Willis, J. E., Campbell, J. P., & Pistilli, M. D. (2013). Ethics, big data, and analytics: A model for application. Retrieved May 17, 2016, from
  150. Willis, J. E., Quick, J., & Hickey, D. T. (2015). Digital badges and ethics The uses of individual learning data in social contexts. In D. T. Hickey, J. Jovanovic, S. Lonn, & J. E. Willis (Eds.), Proceedings of the open badges in education (OBIE 2015) workshop. Poughkeepsie, New York, USA: Ceur-ws.Google Scholar
  151. Wingate, U. (2006). Doing away with ‘study skills’. Teaching in Higher Education, 11(4), 457–469. doi: 10.1080/13562510600874268.CrossRefGoogle Scholar
  152. Wolff, A., Zdrahal, Z., Herrmannova, D., Kuzilek, J., & Hlosta, M. (2014). Developing predictive models for early detection of at-risk students on distance learning modules. In Machine learning and learning analytics workshop at the 4th international conference on learning analytics and knowledge (LAK14). Indianapolis, Indiana, USA.Google Scholar
  153. Wolff, A., Zdrahal, Z., Nikolov, A., & Pantucek, M. (2013). Improving retention: Predicting at-risk students by analysing clicking behaviour in a virtual learning environment. In LAK ‘13 Proceedings of the 3rd international conference on learning analytics and knowledge (pp. 145–149). New York: ACM.Google Scholar
  154. Wright, C. V., & O’Shea, K. (2014). Digital badges and outcomes-based learning. Retrieved May, 24, 2016, from
  155. Wu, M., Whiteley, D., & Sass, M. (2015). From girl scout to grown up: Emerging applications of digital badges in higher education. The Online Journal of Distance Education and e-Learning, 3(2), 48–52.Google Scholar
  156. Yorke, M. (2000). Smoothing the transition into higher education: what can be learned from student non-completion? Australasian Association for Institutional Research Journal, 9(1), 35–47.Google Scholar
  157. Yorke, M., & Longden, B. (2008). The first-year experience of higher education in the UK. York: The Higher Education Academy.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.Applied Teaching and Learning ResearchUniversity of PotsdamPotsdamGermany

Personalised recommendations