Skip to main content
SpringerLink
Log in

Learning Analytics

Spezielle Forschungsmethoden in der Bildungstechnologie

  • Living reference work entry
  • First Online:
Book cover Lernen mit Bildungstechnologien

Part of the book series: Springer Reference Psychologie ((SRP))

Zusammenfassung

Der Forschungsbereich um Learning Analytics hat sich in den vergangenen fünf Jahren rasant entwickelt. Learning Analytics verwenden statische Daten von Lernenden und dynamische in Lernumgebungen gesammelte Daten über Aktivitäten (und den Kontext) des Lernenden, um diese in nahezu Echtzeit zu analysieren und zu visualisieren, mit dem Ziel der Modellierung und Optimierung von Lehr-Lernprozessen und Lernumgebungen. Learning Analytics kann sowohl auf Kursebene als auch auf curricularer Ebene sowie institutionsweit bzw. -übergreifend implementiert werden. Trotz der großen Aufmerksamkeit für das Thema Learning Analytics in der Wissenschaft steckt die praktische Anwendung von Learning Analytics noch in den Anfängen. Dennoch müssen Bildungsinstitutionen bereits jetzt Kapazitäten entwickeln, um der aktuellen Entwicklung folgen zu können. Es bleibt zu erwarten, dass neben datenschutzrechtlichen Regelungen in der Verwendung von Learning Analytics auch technische Standards zum Austausch von Daten aus dem Bildungskontext entwickelt werden.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Notes

  1. 1.

    http://www.open.ac.uk/students/charter/essential-documents/ethical-use-student-data-learning-analytics-policy.

  2. 2.

    http://www.ed.ac.uk/information-services/learning-technology/learning-analytics.

  3. 3.

    http://bits.blogs.nytimes.com/2014/04/21/inbloom-student-data-repository-to-close/?_r=1.

Literatur

  • Bellin-Mularski, N., & Ifenthaler, D. (2014). Learning analytics: Datenanalyse zur Unterstützung von Lehren und Lernen in der Schule. SchulVerwaltung NRW, 25(11), 300–303.

    Google Scholar 

  • Berg, A., Scheffel, M., Ternier, S., Drachsler, H., & Specht, M. (2016). Dutch cooking with xAPI recipes – The good, the bad, and the consistent. 16th IEEE international conference on advancing learning technologies (ICALT 2016). Austin.

    Google Scholar 

  • Berland, M., Baker, R. S. J. d., & Bilkstein, P. (2014). Educational data mining and learning analytics: Applications to constructionist research. Technology, Knowledge and Learning, 19(1–2), 205–220. https://doi.org/10.1007/s10758-014-9223-7.

    Article  Google Scholar 

  • Buckingham Shum, S., & Ferguson, R. (2012). Social learning analytics. Educational Technology & Society, 15(3), 3–26.

    Google Scholar 

  • d’Aquin, M., Dietze, S., Herder, E., Drachsler, H., & Taibi, D. (2014). Using linked data in learning analytics. eLearning papers, 36. http://www.openeducationeuropa.eu/en/download/file/fid/33993. Zugegriffen am 12.10.2017.

  • Di Mitri, D., Scheffel, M., Drachsler, H., Börner, D., Ternier, S., & Specht, M. (2017). Learning pulse: A machine learning approach for predicting performance in self-regulated learning using multimodal data. 7th learning analytics and knowledge conference 2017. Vancouver.

    Google Scholar 

  • Drachsler, H. & Greller, W. (2016). Privacy and analytics – It’s a DELICATE issue. A checklist to establish trusted learning analytics. 6th learning analytics and knowledge conference 2016. (S. 89–98), 25–29 April 2016. Edinburgh/New York: ACM.

    Google Scholar 

  • Drachsler, H., & Kalz, M. (2016). The MOOC and learning analytics innovation cycle (MOLAC): A reflective summary of ongoing research and its challenges. Journal of Computer Assisted Learning, 32(3), 281–290. https://doi.org/10.1111/jcal.12135.

    Article  Google Scholar 

  • Drachsler, H., Stoyanov, S., & Specht, M. (2014). The impact of learning analytics on the Dutch education system. Presentation given at the 4th international conference on learning analytics and knowledge. Indianapolis.

    Google Scholar 

  • Drachsler, H., Verbert, K., Santos, O. C., & Manouselis, N. (2015). Panorama of recommender systems to support learning. In F. Rici, L. Rokach & B. Shapira (Hrsg.), 2nd handbook on recommender systems (S. 421–451). USA: Springer. https://doi.org/10.1007/978-1-4899-7637-6_12.

    Chapter  Google Scholar 

  • Dyckhoff, A. L., Zielke, D., Bültmann, M., Chatti, M. A., & Schroeder, U. (2012). Design and implementation of a learning analytics toolkit for teachers. Educational Technology & Society, 15(3), 58–76.

    Google Scholar 

  • Endsley, M. R. (1995). Toward a theory of situation awareness in dynamic systems. Human Factors, 37, 32–64.

    Article  Google Scholar 

  • Fazeli, S., Loni, B., Drachsler, H., & Sloep, P. (2014). Which recommender system can best fit social learning platforms? Presentation given at the 9th European conference on technology enhanced learning (EC-TEL2014). Graz.

    Google Scholar 

  • Gibson, D. C., & Ifenthaler, D. (2017). Preparing the next generation of education researchers for big data in higher education. In B. Kei Daniel (Hrsg.), Big data and learning analytics: Current theory and practice in higher education (S. 29–42). New York: Springer.

    Chapter  Google Scholar 

  • Greller, W., & Drachsler, H. (2012). Translating learning into numbers: A generic framework for learning analytics Educational Technology & Society, 15(3), 42–57.

    Google Scholar 

  • Ifenthaler, D. (2012). Determining the effectiveness of prompts for self-regulated learning in problem-solving scenarios. Journal of Educational Technology & Society, 15(1), 38–52.

    Google Scholar 

  • Ifenthaler, D. (2014). AKOVIA: Automated knowledge visualization and assessment. Technology, Knowledge and Learning, 19(1–2), 241–248. https://doi.org/10.1007/s10758-014-9224-6.

    Article  Google Scholar 

  • Ifenthaler, D. (2015). Learning analytics. In J. M. Spector (Hrsg.), The SAGE encyclopedia of educational technology (Bd. 2, S. 447–451). Thousand Oaks: Sage.

    Google Scholar 

  • Ifenthaler, D. (2017). Are higher education institutions prepared for learning analytics? TechTrends, 61(4), 366–371. https://doi.org/10.1007/s11528-016-0154-0.

    Article  Google Scholar 

  • Ifenthaler, D., & Schumacher, C. (2016a). Learning Analytics im Hochschulkontext. WiSt – Wirtschaftswissenschaftliches Studium, 4, 172–177.

    Google Scholar 

  • Ifenthaler, D., & Schumacher, C. (2016b). Student perceptions of privacy principles for learning analytics. Educational Technology Research and Development, 64(5), 923–938. https://doi.org/10.1007/s11423-016-9477-y.

    Article  Google Scholar 

  • Ifenthaler, D., & Tracey, M. W. (2016). Exploring the relationship of ethics and privacy in learning analytics and design: Implications for the field of educational technology. Educational Technology Research and Development, 64(5), 877–880. https://doi.org/10.1007/s11423-016-9480-3.

    Article  Google Scholar 

  • 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. https://doi.org/10.1007/s10758-014-9226-4.

    Article  Google Scholar 

  • Ifenthaler, D., Bellin-Mularski, N., & Mah, D.-K. (2015). Internet: Its impact and its potential for learning and instruction. In J. M. Spector (Hrsg.), The SAGE encyclopedia of educational technology (Bd. 1, S. 416–422). Thousand Oaks: Sage.

    Google Scholar 

  • Jivet, I., Scheffel, M., Drachsler, H., & Specht, M. (2017). Awareness is not enough. Pitfalls of learning analytics dashboards in the educational practise. 12th European conference on technology-enhanced learning. Tallinn, 12–15 Sept. 2017.

    Google Scholar 

  • Johnson, L., Adams Becker, S., Cummins, M., Freeman, A., Ifenthaler, D., & Vardaxis, N. (2013). Technology outlook for Australian tertiary education 2013–2018: An NMC horizon project regional analysis. Austin: The New Media Consortium.

    Google Scholar 

  • Long, P. D., & Siemens, G. (2011). Penetrating the fog: Analytics in learning and education. Educause Review, 46(5), 31–40.

    Google Scholar 

  • Macfadyen, L., & Dawson, S. (2012). Numbers are not enough. Why e-Learning analytics failed to inform an institutional strategic plan. Educational Technology & Society, 15(3), 149–163.

    Google Scholar 

  • New York Times. (2014). InBloom Student Data Repository to Close, 21 April 2014. http://bits.blogs.nytimes.com/2014/04/21/inbloom-student-data-repository-to-close/?_r=0. Zugegriffen am 12.10.2017.

  • Pijeira-díaz, H. J., Drachsler, H., Järvelä, S., & Kirschner, P. A. (2016). Investigating collaborative learning success with physiological coupling indices based on electrodermal activity. 6th learning analytics and knowledge conference 2016. 25–29 April 2016. Edinburgh.

    Google Scholar 

  • Pistilli, M. D., & Arnold, K. E. (2010). Purdue signals: Mining real-time academic data to enhance student success. About campus: Enriching the student learning experience, 15(3), 22–24.

    Google Scholar 

  • Scheffel, M. (2017). The evaluation framework for learning analytics. Doctoral thesis. Heerlen: Open Universiteit (Welten Institute, Research centre for learning, Teaching and technology). http://dspace.ou.nl/handle/1820/8259.

  • Scheffel, M., Drachsler, H., Stoyanov, S., & Specht, M. (2014). Quality indicators for learning analytics. Educational Technology & Society, 17(4), 117–132.

    Google Scholar 

  • Scheffel, M., Drachsler, H., de Kraker, J., Kreijns, K., Slootmaker, A., & Specht, M. (2016). Widget, widget on the wall, am I performing well at all? IEEE Transactions on Learning Technologies, 10(1), 42–52. https://doi.org/10.1109/TLT.2016.2622268.

    Article  Google Scholar 

  • Scheffel, M., Drachsler, H., Kreijns, K., de Kraker, J., & Specht, M. (2017a). Widget, widget as you lead, I am performing well indeed! – Using results from a formative offline study to inform an empirical online study about a learning analytics widget in a collaborative learning environment. Proceedings of the (LAK’17). Vancouver: ACM.

    Google Scholar 

  • Scheffel, M., Drachsler, H., Toisoul, C., Ternier, S., & Specht, M. (2017b). The Proof of the pudding: Examining validity and reliability of the evaluation framework for learning analytics. In E. Lavoué, H. Drachsler, K. Verbert, J. Broisin & M. Pérez-Sanagustín (Hrsg.), Data driven approaches in digital education. Proceedings of the 12th European conference on technology enhanced learning (EC-TEL 2017), LNCS (Bd. 10474, S. 194–208). Berlin/Heidelberg: Springer.

    Google Scholar 

  • Siemens, G., Dawson, S., & Lynch, G. (2014). Improving the quality and productivity of the higher education sector – Policy and strategy for systems-level deployment of learning analytics. Canberra, Australia: Office of Learning and Teaching, Australian Government. http://solaresearch.org/Policy_Strategy_Analytics.pdf.

  • Tabuenca, B., Kalz, M., Drachsler, H., & Specht, M. (2015). Time will tell: The role of mobile learning analytics in self-regulated learning. Computers & Education, 89, 53–74.

    Article  Google Scholar 

  • Verbert, K., Manouselis, N., Drachsler, H., & Duval, E. (2012). Dataset-driven research to support learning and knowledge analytics. Educational Technology & Society, 15(3), 133–148.

    Google Scholar 

  • Zimmerman, B. J. (1995). Self-regulation involves more than metacognition: A social cognitive perspective. Educational Psychologist, 30(4), 217–221.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Learning, Design and Technology, Universität Mannheim, Mannheim, Deutschland

    Dirk Ifenthaler

  2. Deutsches Institut für Internationale Pädagogsche Forschung, Goethe Universität Frankfurt am Main, Frankfurt, Deutschland

    Hendrik Drachsler

Authors
  1. Dirk Ifenthaler
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hendrik Drachsler
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dirk Ifenthaler .

Editor information

Editors and Affiliations

  1. Universität des Saarlandes, Saarbrücken, Germany

    Helmut Niegemann

  2. Lehrstuhl für Bildungstechnologie, Universität des Saarlandes, Saarbrücken, Saarland, Germany

    Armin Weinberger

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer-Verlag GmbH Deutschland, ein Teil von Springer Nature

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Ifenthaler, D., Drachsler, H. (2018). Learning Analytics. In: Niegemann, H., Weinberger, A. (eds) Lernen mit Bildungstechnologien. Springer Reference Psychologie . Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-54373-3_42-1

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-54373-3_42-1

  • Received:

  • Accepted:

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-54373-3

  • Online ISBN: 978-3-662-54373-3

  • eBook Packages: Springer Referenz Psychologie

Publish with us

Policies and ethics

Search

Navigation