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IT-gestütztes Peer-Assessment zur Schulung von Kompetenzen in der Lehre

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Chancen und Herausforderungen des digitalen Lernens

Part of the book series: Kompetenzmanagement in Organisationen ((KOOR))

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Zusammenfassung

Universitäten sind heutzutage mit einer immer größeren Anzahl an Studierenden konfrontiert. Entsprechend findet nur wenig oder keine Interaktion zwischen Lehrenden und Studierenden statt, und es kommt zu wenig Feedback. Dies ist oftmals kritisch, da besonders Feedback und die direkte Interaktion wichtig für den Lernerfolg und die Zufriedenheit für beide Seiten sind. Der Einsatz von IT-gestütztem Peer-Assessment (ITPA) ist eine Lösung, um die Interaktion und das Feedback mit Studierenden in einen Lernprozess zu integrieren. Dabei beurteilen Lernende wechselseitig die Qualität der Arbeit von anderen. In dem vorliegenden Kapitel wird aufgezeigt, wie ITPA in eine Blended-Learning-Massenlehrveranstaltung integriert werden kann. Die Ergebnisse zeigen, dass ITPA eine wichtige Rolle in Bezug auf den wahrgenommenen Lernerfolg und die Zufriedenheit spielt. Aufgezeigt wird, wie Massenlehrveranstaltungen ressourcenschonend bereichert werden können.

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Literatur

  1. Alonso, F., Manrique, D., & Viñes, J. M. (2009). A moderate constructivist e-learning instructional model evaluated on computer specialists. Computers & Education, 53(1), 57–65.

    Google Scholar 

  2. Anderson, L., Krathwohl, D., Airasian, P. W., Cruikshank, K. A., Mayer, R. E., Pintrich, P., et al. (2001). A taxonomy for learning, teaching, and assessing: A revision of bloom’s taxonomy of educational objectives. New York: Addison Wesley Longmann.

    Google Scholar 

  3. Bandura, A. (1977). Social learning theory prentice-hall. New Jersey: Englewood Cliffs.

    Google Scholar 

  4. Bauer, C., Figl, K., Derntl, M., Beran, P. P., & Kabicher, S. (2009). Der Einsatz von Online-PeerReviews als kollaborative Lernform. Wirtschaftsinformatik, 2, 421–430.

    Google Scholar 

  5. Benbunan-Fich, R. (2010). Is self-reported learning a proxy metric for learning? Perspectives from the information systems literature. Academy of Management Learning & Education, 9, 321–328.

    Google Scholar 

  6. Bernard, R. M., Abrami, P. C., Borokhovski, E., Wade, C. A., Tamim, R. M., Surkes, M. A., et al. (2009). A meta-analysis of three types of interaction treatments in distance education. Review of Educational Research, 79(3), 1243–1289.

    Article  Google Scholar 

  7. Bitzer, P., Söllner, M., & Leimeister, J. M. (2016). Design principles for high-performance blended learning services delivery – The case of software trainings in Germany. Business & Information Systems Engineering (BISE), 58(2), 135–149.

    Google Scholar 

  8. Bligh, D. (2000). What’s the use of lectures?. San Francisco: Jossey-Bass.

    Google Scholar 

  9. Bloom, B. S., & Krathwohl, D. R. (1956). Taxonomy of educational objectives. The classification of educational goals, by a committee of college and university examiners. Handbook I, Cognitive domain. New York: Longmans, Green & Co.

    Google Scholar 

  10. Bostock, S. J. (2004). Motivation and electronic assessment. Effective learning and teaching in computing (S. 86–99).

    Google Scholar 

  11. Boud, D., & Falchikov, N. (2007). Rethinking assessment in higher education: Learning for the longer term. Abingdon: Routledge.

    Google Scholar 

  12. Braun, E., Gusy, B., Leidner, B., & Hannover, B. (2008). Das Berliner Evaluationsinstrument für selbsteingeschätzte, studentische Kompetenzen (BEvaKomp). Diagnostica, 54,30–42.

    Google Scholar 

  13. Butler, D. L. (2003). Structuring instruction to promote self-regulated learning by adolescents and adults with learning disabilities. Exceptionality, 11(1), 39–60.

    Article  Google Scholar 

  14. Bühner, M. (2011). Einführung in die Test-und Fragebogenkonstruktion. München: Pearson.

    Google Scholar 

  15. Chang, C.-C., Tseng, K.-H., Chou, P.-N., & Chen, Y.-H. (2011). Reliability and validity of Web-based portfolio peer assessment: A case study for a senior high school’s students taking computer course. Computers & Education, 57(1), 1306–1316.

    Google Scholar 

  16. Chang, C.-C., Tseng, K.-H., & Lou, S.-J. (2012). A comparative analysis of the consistency and difference among teacher-assessment, student self-assessment and peer-assessment in a Web-based portfolio assessment environment for high school students. Computers & Education, 58(1), 303–320.

    Google Scholar 

  17. Chen, C.-H. (2010). The implementation and evaluation of a mobile self-and peer-assessment system. Computers & Education, 55(1), 229–236.

    Article  Google Scholar 

  18. Cheng, W., & Warren, M. (1997). Having second thoughts: Student perceptions before and after a peer assessment exercise. Studies in Higher Education, 22(2), 233–239.

    Google Scholar 

  19. Chickering, A. W., & Gamson, Z. F. (1989). Seven principles for good practice in undergraduate education. Biochemical Education, 17(3), 140–141.

    Google Scholar 

  20. Chiru, C., Ciuchete, S. G., Lefter, G. G., & Paduretu, E. (2012). A cross country study on university graduates key competencies. An employer‘s perspective. Procedia – Social and Behavioral Sciences, 46, 4258–4262.

    Google Scholar 

  21. Darling-Hammond, L., Ancess, J., & Falk, B. (1995). Authentic assessment in action: Studies of schools and students at work. New York: Teachers College Press.

    Google Scholar 

  22. Davenport, T. H. (1993). Process innovation: Reengineering work through information technology. Boston: Harvard Business School Press.

    Google Scholar 

  23. Davenport, T. H., & Short, J. (2003). The new industrial engineering: Information technology and business process redesign. In M. Lewis & N. Slack (Hrsg.), Operations management: Critical perspectives on business and management (S. 61–118). London: Routledge.

    Google Scholar 

  24. De Raadt, M., Toleman, M., & Watson, R. (2005). Electronic peer review: A large cohort teaching themselves? In Proceedings ASCILITE, Brisbane, Australia.

    Google Scholar 

  25. Delen, E., Liew, J., & Willson, V. (2014). Effects of interactivity and instructional scaffolding on learning: Self-regulation in online video-based environments. Computers & Education, 78,312–320.

    Google Scholar 

  26. Dochy, F., Segers, M., & Sluijsmans, D. (1999). The use of self-, peer and co-assessment in higher education: A review. Studies in Higher Education, 24(3), 331–350.

    Google Scholar 

  27. Doiron, G. (2003). The value of online student peer review, evaluation and feedback in higher education. CDTL Brief, 6(9), 1–2.

    Google Scholar 

  28. Duncan-Howell, J. A., & Lee, K.-T. (2007). M-Learning – Innovations and initiatives: Finding a place for mobile technologies within tertiary educational settings. Singapore: Ascilite.

    Google Scholar 

  29. Dyson, L. E., Litchfield, A., Raban, R., & Tyler, J. (2009). Interactive classroom mLearning and the experiential transactions between students and lecturer. Ascilite.

    Google Scholar 

  30. Ebert-May, D., Brewer, C., & Allred, S. (1997). Innovation in large lectures: Teaching for active learning. Bioscience, 47(9), 601–607.

    Google Scholar 

  31. Ertmer, P. A., & Newby, T. J. (1996). The expert learner: Strategic, self-regulated, and reflective. Instructional science, 24(1), 1–24.

    Google Scholar 

  32. Falchikov, N. (1995). Peer feedback marking: Developing peer assessment. Programmed Learning, 32(2), 175–187.

    Article  Google Scholar 

  33. Falchikov, N., & Goldfinch, J. (2000). Student peer assessment in higher education: A meta-analysis comparing peer and teacher marks. Review of Educational Research, 70(3), 287–322.

    Google Scholar 

  34. Fortes, P. C., & Tchantchane, A. (2010). Dealing with large classes: A real challenge. Procedia – Social and Behavioral Sciences, 8, 272–280.

    Google Scholar 

  35. Gagné, E. D., Yekovich, C. W., & Yekovich, F. R. (1993). The cognitive psychology of school learning. New York: HarperCollins College.

    Google Scholar 

  36. Garrison, D. R., & Shale, D. (1990). A new framework and perspective. In D. R. Garrison & D. Shale (Hrsg.), Education at a distance: From issues to practice (S. 123–133). Malabar: RE Krieger Publishing Company.

    Google Scholar 

  37. Gregor, S., & Hevner, A. R. (2013). Positioning and presenting design science research for maximum impact. MIS Quarterly, 37(2), 337–356.

    Google Scholar 

  38. Gupta, S., & Bostrom, R. G. (2009). Technology-mediated learning: A comprehensive theoretical model. Journal of the Association for Information Systems, 10(9), 686–714.

    Google Scholar 

  39. Hagstrom, F. (2006). Formative learning and assessment. Communication Disorders Quarterly, 28(1), 24–36.

    Article  Google Scholar 

  40. Hara, N. (2000). Student distress in a web-based distance education course. Information, Communication & Society, 3(4), 557–579.

    Article  Google Scholar 

  41. Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004). Design science in information systems research. MIS Quarterly, 28(1), 75–105.

    Google Scholar 

  42. Hovardas, T., Tsivitanidou, O. E., & Zacharia, Z. C. (2014). Peer versus expert feedback: An investigation of the quality of peer feedback among secondary school students. Computers & Education, 71,133–152.

    Google Scholar 

  43. Hull, E., Jackson, K., & Dick, J. (2010). Requirements engineering.London: Springer Science & Business Media.

    Google Scholar 

  44. Hwang, G.-J., Hung, C.-M., & Chen, N.-S. (2014). Improving learning achievements, motivations and problem-solving skills through a peer assessment-based game development approach. Educational Technology Research and Development, 62(2), 129–145.

    Google Scholar 

  45. Jaillet, A. (2009). Can online peer assessment be trusted? Educational Technology & Society, 12(4), 257–268.

    Google Scholar 

  46. Johnson, L., Adams, S., Cummins, M., Estrada, V., Freeman, A., & Hall, C. (2016). NMC horizon report: 2016 higher education edition. Austin: The new media consortium.

    Google Scholar 

  47. Kulkarni, C., Wei, K. P., Le, H., Chia, D., Papadopoulos, K., Cheng, J., et al. (2013). Peer and self assessment in massive online classes. ACM Transactions on Computer-Human Interaction, 20(6), 33.

    Article  Google Scholar 

  48. Lehmann, K. (2017). Fostering Interaction and Feedback in Higher Education Large-Scale Lectures – Design and evaluation of technology-mediated Self- and Peer Assessments (PhD dissertation) (Leimeister, J. M., Ed.). Universität Kassel, Kassel, Germany.

    Google Scholar 

  49. Lehmann, K., & Leimeister, J.-M. (2015). Theory-driven design of an IT-based peer assessment to assess high cognitive levels of educational objectives in large-scale learning Services 23rd European Conference on Information Systems (ECIS 2015), Münster, Germany.

    Google Scholar 

  50. Lehmann, K., & Söllner, M. (2014). Theory-driven design of a mobile-learning application to support different interaction types in large-scale lectures. European conference on information systems (ECIS), Tel Aviv, Israel.

    Google Scholar 

  51. Lehmann, K., Oeste, S., Janson, A., Söllner, M., & Leimeister, J. M. (2015). Flipping the Classroom – IT-unterstützte Lerneraktivierung zur Verbesserung des Lernerfolges einer universitären Massenlehrveranstaltung. HMD Praxis der Wirtschaftsinformatik, 52(1), 81–95. https://doi.org/10.1365/s40702-014-0102-4.

    Article  Google Scholar 

  52. Lehmann, K., Oeste, S., Janson, A., Söllner, M., & Leimeister, J. M. (2015). Flipping the Classroom – IT-unterstützte Lerneraktivierung zur Verbesserung des Lernerfolges einer universitären Massenlehrveranstaltung. HMD: Praxis der Wirtschaftsinformatik, 51(1), 81–95. ISSN 1436-3011.

    Google Scholar 

  53. Lehmann, K., Söllner, M., Blohm, I., & Leimeister, J. M. (2016). How many peer assessors are required for assessment on another peer’s work? In 76th Academy of Management Annual Meeting (AOM) 2016 “Making Organizations Meaningful”, – Anaheim.

    Google Scholar 

  54. Leijen, Ä., Lam, I., Wildschut, L., Simons, P. R.-J., & Admiraal, W. (2009). Streaming video to enhance students’ reflection in dance education. Computers & Education, 52(1), 169–176.

    Google Scholar 

  55. Leimeister, J. M. (2012). Dienstleistungsengineering und-management. Berlin: Springer.

    Google Scholar 

  56. Liang, J.-C., & Tsai, C.-C. (2010). Learning through science writing via online peer assessment in a college biology course. The Internet and Higher Education, 13(4), 242–247.

    Google Scholar 

  57. Liu, J., & Sadler, R. W. (2003). The effect and affect of peer review in electronic versus traditional modes on L2 writing. Journal of English for Academic Purposes, 2(3), 193–227.

    Google Scholar 

  58. Mintzes, J. J., Wandersee, J. H., & Novak, J. D. (2005). Assessing science understanding: A human constructivist view. San Diego: Academic.

    Google Scholar 

  59. Moore, M. G. (1989). Three types of interaction. The American Journal of Distance Education, 3(2), 1–6.

    Google Scholar 

  60. Moore, A., Masterson, J. T., Christophel, D. M., & Shea, K. A. (1996). College teacher immediacy and student ratings of instruction. Communication Education, 45(1), 29–39.

    Google Scholar 

  61. Nicol, D. J., & Macfarlane-Dick, D. (2006). Formative assessment and self-regulated learning: A model and seven principles of good feedback practice. Studies in Higher education, 31(2), 199–218.

    Google Scholar 

  62. Oeste, S., Lehmann, K., Janson, A., & Leimeister, J. M. (2014). Flipping the IS Classroom – Theory-Driven Design for Large-Scale Lectures. In International Conference on Information Systems (ICIS), Auckland, New Zealand.

    Google Scholar 

  63. Oeste, S., Lehmann, K., Janson, A., Söllner, M. & Leimeister, J. M. (2015). Redesigning university large scale lectures: How to activate the learner. In Academy of Management Annual Meeting (AOM). Vancouver, BC, Canada.

    Google Scholar 

  64. Peffers, K., Tuunanen, T., Rothenberger, M. A., & Chatterjee, S. (2007). A design science research methodology for information systems research. Journal of Management Information Systems, 24(3), 45–77.

    Google Scholar 

  65. Picciano, A. G. (2002). Beyond student perceptions: Issues of interaction, presence, and performance in an online course. Journal of Asynchronous learning networks, 6(1), 21–40.

    Google Scholar 

  66. Piech, C., Huang, J., Chen, Z., Do, C., Ng, A., & Koller, D. (2013). Tuned models of peer assessment in MOOCs. arXiv preprint arXiv:1307.2579.

  67. Rietsche, R., Lehmann, K., Haas, P., & Söllner, M. (2017). The twofold value of IT-based peer assessment in management information systems education. In 13th International Conference on Wirtschaftsinformatik (WI), – St. Gallen, Switzerland.

    Google Scholar 

  68. Rushton, C. (1993). Peer assessment in a collaborative hypermedia environment: A case study. Journal of Computer-Based Instruction, 20(3), 75–80.

    Google Scholar 

  69. Sadler, P. M., & Good, E. (2006). The impact of self-and peer-grading on student learning. Educational Assessment, 11(1), 1–31.

    Google Scholar 

  70. Schrum, L., & Berge, Z. L. (1997). Creating student interaction within the educational experience: A challenge for online teachers. Canadian Journal of Educational Communication, 26(3), 133–144.

    Google Scholar 

  71. Schwab, K., & Samans, R. (2016). The future of jobs. Employment, skills and workforce strategy for the fourth industrial revolution. World Economic Forum.

    Google Scholar 

  72. Sims, R. (2003). Promises of interactivity: Aligning learner perceptions and expectations with strategies for flexible and online learning. Distance Education, 24(1), 87–103.

    Article  Google Scholar 

  73. Snell, Y. S., & Linda, S. (1999). Interactive lecturing: Strategies for increasing participation in large group presentations. Medical Teacher, 21(1), 37–42.

    Google Scholar 

  74. Strijbos, J. W., Ochoa, T. A., Sluijsmans, D. M., Segers, M. S., & Tillema, H. H. (2009). Fostering interactivity through formative peer assessment in (web-based) collaborative learning environments. In Cognitive and emotional processes in web-based education: Integrating human factors and personalization (S. 375–395). IGI Global.

    Google Scholar 

  75. Sullivan, N., & Pratt, E. (1996). A comparative study of two ESL writing environments: A computerassisted classroom and a traditional oral classroom. System, 24(4), 491–501.

    Google Scholar 

  76. Sung, Y.-T., Chang, K.-E., Chiou, S.-K., & Hou, H.-T. (2005). The design and application of a web-based self- and peer-assessment system. Computers & Education, 45(2), 187–202.

    Google Scholar 

  77. Tahir, I. H. (2012). A study on peer evaluation and its influence on college ESL students. Procedia Social and Behavioral Sciences, 68,192–201.

    Article  Google Scholar 

  78. Thurmond, V., & Wambach, K. (2004). Understanding interactions in distance education: A review of the literature. International Journal of Instructional Technology and Distance Learning, 1(1), 9–26.

    Google Scholar 

  79. Topping, K. J. (2005). Trends in peer learning. Educational psychology, 25(6), 631–645.

    Article  Google Scholar 

  80. Tseng, S.-C., & Tsai, C.-C. (2007). Online peer assessment and the role of the peer feedback: A study of high school computer course. Computers & Education, 49(4), 1161–1174.

    Google Scholar 

  81. Tsivitanidou, O. E., Zacharia, Z. C., & Hovardas, T. (2011). Investigating secondary school students’ unmediated peer assessment skills. Learning and Instruction, 21(4), 506–519.

    Google Scholar 

  82. Tuzi, F. (2004). The impact of e-feedback on the revisions of L2 writers in an academic writing course. Computers and Composition, 21(2), 217–235.

    Article  Google Scholar 

  83. Van De Grift, T., Wolfman, S. A., Yasuhara, K., & Anderson, R. J. (2002). Promoting interaction in large classes with a computer-mediated feedback system (S. 1–10). Washington State University.

    Google Scholar 

  84. Van Den Boom, G., Paas, F., & van Merriënboer, J. J. (2007). Effects of elicited reflections combined with tutor or peer feedback on self-regulated learning and learning outcomes. Learning and Instruction, 17(5), 532–548.

    Google Scholar 

  85. Veerman, A. L., Andriessen, J. E. B., & Kanselaar, G. (2000). Learning through synchronous electronic discussion. Computers & Education, 34(3–4), 269–290.

    Google Scholar 

  86. Vom Brocke, J., White, C., Walker, U., & Vom Brocke, C. (2010). Making User-Generated Content communities work in higher education-the importance of setting incentives. Changing cultures in higher education, Moving ahead to future learning (S. 149–166). Berlin: Springer.

    Google Scholar 

  87. Wang, M. C., Haertel, G. D., & Walberg, H. J. (1990). What influences learning? A content analysis of review literature. The Journal of Educational Research, 84(1), 30–43.

    Google Scholar 

  88. Winter, R. (2008). Design science research in Europe. European Journal of Information Systems, 17(5), 470–475.

    Article  Google Scholar 

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Authors and Affiliations

  1. Kassel, Deutschland

    Katja Lehmann

  2. Fachgebiet Wirtschaftsinformatik und Systementwicklung, Universität Kassel, Kassel, Deutschland

    Matthias Söllner

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  1. Katja Lehmann
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Correspondence to Matthias Söllner .

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  1. Fachgebiet Wirtschaftsinformatik, Universität Kassel, Kassel, Hessen, Germany

    Jan Marco Leimeister

  2. Fachgebiet Kommunikationstechnik, Universität Kassel, Kassel, Hessen, Germany

    Klaus David

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Lehmann, K., Söllner, M. (2019). IT-gestütztes Peer-Assessment zur Schulung von Kompetenzen in der Lehre. In: Leimeister, J., David, K. (eds) Chancen und Herausforderungen des digitalen Lernens. Kompetenzmanagement in Organisationen. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-59390-5_6

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