Top

Technology, Knowledge and Learning

Published in:

23-02-2023 | Original research

Mediating Teacher Professional Learning with a Learning Analytics Dashboard and Training Intervention

Authors: Manisha Khulbe, Kairit Tammets

Published in: Technology, Knowledge and Learning | Issue 3/2023

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

Insights derived from classroom data can help teachers improve their practice and students’ learning. However, a number of obstacles stand in the way of widespread adoption of data use. Teachers are often sceptical about the usefulness of data. Even when willing to work with data, they often do not have the relevant skills. Tools for analysis of learning data can, theoretically, aid teachers in data use, but often fall short of their potential as they are commonly designed without reference to educational theory and rarely consider end-user’s needs. Keeping these challenges in mind, we designed a professional development program that aimed at, among other things, improving teachers’ beliefs regarding data and their data literacy skills. After the training, we found that teachers had more positive attitudes regarding data. However, some data literacy skills proved quite difficult to learn. We present and analyse our intervention here and forward a proposal for improving the effectiveness of data use interventions by leveraging theory-based Learning Analytics (LA) dashboards as mediating tools that scaffold teachers’ acquisition of new knowledge and skills during and beyond the intervention.

previous article Use of Predictive Analytics within Learning Analytics Dashboards: A Review of Case Studies

next article Digitalisation in the Curricula of Vocational Schools: Text Mining as an Instrument of Curricula Analysis

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Avramides, K., Hunter, J., Oliver, M., & Luckin, R. (2014). A method for teacher inquiry in cross-curricular projects: Lessons from a case study. British Journal of Educational Technology, 46(2), 249–264. https://doi.org/10.1111/bjet.12233.CrossRef

Bocala, C., & Boudett, K. P. (2015). Teaching educators habits of mind for using data wisely. Teachers College Record, 117(4), 1–20. https://doi.org/10.1177/016146811511700409.CrossRef

Buckingham Shum, S., Ferguson, R., & Martinez-Maldonado, R. (2019). Human-centred learning analytics. Journal of Learning Analytics, 6(2), 1–9. https://doi.org/10.18608/jla.2019.62.1.CrossRef

Carlson, D., Borman, G. D., & Robinson, M. (2011). A Multistate District-Level Cluster Randomized Trial of the Impact of Data-Driven Reform on Reading and Mathematics Achievement.Educational Evaluation and Policy Analysis, 33(3),378–398. https://doi.org/10.3102/0162373711412765

Datnow, A., & Hubbard, L. (2015). Teachers’ use of assessment data to inform instruction: Lessons from the past and prospects for the future.Teachers College Record, 117(4),1–26. https://doi.org/10.1177/016146811511700408

Dollinger, M., & Lodge, J. M. (2018). Co-Creation Strategies for Learning Analytics. Proceedings of the 8th International Conference on Learning Analytics and Knowledge (LAK ’18), 97–101. https://doi.org/10.1145/3170358.3170372

Ebbeler, J., Poortman, C. L., Schildkamp, K., & Pieters, J. M. (2017). The effects of a data use intervention on educators’ satisfaction and data literacy.Educational Assessment, Evaluation and Accountability, 29,83–105. https://doi.org/10.1007/s11092-016-9251-z

Field, A. (2013). Discovering statistics using IBM SPSS statistics. Sage Publications.

Gašević, D., Dawson, S., & Siemens, G. (2015). Let’s not forget: learning analytics are about learning. TechTrends, 59(1), 64–71. https://doi.org/10.1007/s11528-014-0822-x.CrossRef

Hamilton, L., Halverson, R., Jackson, S. S., Mandinach, E., Supovitz, J. A., & Wayman, J. C. (2009). Using student achievement data to support instructional decision making.National Center for Education Evaluation and Regional Assistance, Institute of Education Sciences, U.S. Department of Education.

Hannafin, M., Land, S., & Oliver, K. (1999). Open learning environments: foundations, methods, and models. In C. M. Reigeluth (Ed.), Instructional-design theories and models: a new paradigm of instructional theory (II vol., pp. 115–140). Mahwah, NJ: Lawrence Erlbaum Associates.

Hansen, C. J., & Wasson, B. (2016). Teacher Inquiry into Student Learning: - the TISL Heart Model and Method for use in Teachers’ Professional Development. Nordic Journal of Digital Literacy, 10, 24–49. https://doi.org/10.18261/issn.1891-943x-2016-01-02.CrossRef

Henderson, J., & Corry, M. (2020). Data literacy training and use for educational professionals. Journal of Research in Innovative Teaching & Learning, 14(2), 232–244. https://doi.org/10.1108/JRIT-11-2019-0074.CrossRef

Hoogland, I., Schildkamp, K., van der Kleij, F., Heitink, M., Kippers, W., Veldkamp, B., & Dijkstra, A. M. (2016). Prerequisites for data-based decision making in the classroom: Research evidence and practical illustrations. Teaching and Teacher Education, 60, 377–386. https://doi.org/10.1016/j.tate.2016.07.012.CrossRef

Jimerson, J. B. (2014). Thinking about data: exploring the development of mental models for “data use” among teachers and school leaders. Studies in Educational Evaluation, 42, 5–14. https://doi.org/10.1016/j.stueduc.2013.10.010.CrossRef

Jivet, I., Scheffel, M., Drachsler, H., & Specht, M. (2017). Awareness is not enough: Pitfalls of learning analytics dashboards in the educational practice. In Proceedings of the 12th European Conference on Technology Enhanced Learning (pp. 82–96). Springer.

Johnson, K. E., & Golombek, P. R. (2003). Seeing. Teacher Learning TESOL Quarterly, 37(4), 729–737. https://doi.org/10.2307/3588221.CrossRef

Kippers, W. B., Poortman, C. L., Schildkamp, K., & Visscher, A. J. (2018). Data literacy: What do educators learn and struggle with during a data use intervention?Studies in Educational Evaluation, 56,21–31. https://doi.org/10.1016/j.stueduc.2017.11.001

Koh, E., & Tan, J. P. (2017). Teacher-actionable insights in student engagement: A learning analytics taxonomy. Proceedings of the 25th International Conference on Computers in Education, 319–325.

Lai, M. K., & Schildkamp, K. (2013). Data-based decision making: an overview. In K. Schildkamp, M. K. Lai, & L. Earl (Eds.), Data-based decision making in education: Challenges and opportunities (pp. 9–21). Dordrecht: Springer.CrossRef

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

Mandinach, E. B., & Gummer, E. S. (2016). What does it mean for teachers to be data literate: laying out the skills, knowledge, and dispositions. Teaching and Teacher Education, 60, 366–376. https://doi.org/10.1016/j.tate.2016.07.011.CrossRef

Marsh, J. (2012). Interventions promoting educators’ use of data: research insights and gaps. Teachers College Record, 114(11), 1–47. https://doi.org/10.1177/016146811211401106.CrossRef

Matcha, W., Uzir, N. A., Gašević, D., & Pardo, A. (2020). A systematic review of empirical studies on learning analytics dashboards: a self-regulated learning perspective. IEEE Transactions on Learning Technologies, 13(2), 226–245. https://doi.org/10.1109/TLT.2019.2916802.CrossRef

McNaughton, S., Lai, M. K., & Hsiao, S. (2012). Testing the effectiveness of an intervention model based on data use: a replication series across clusters of schools. School Effectiveness and School Improvement, 23(2), 203–228. https://doi.org/10.1080/09243453.2011.652126.CrossRef

Miller, M. (2009). Achieving a wealth of riches: delivering on the promise of data to transform teaching and learning (policy brief). Alliance for Excellent Education.

Morgan, N., & Killion, J. (2018). Beyond barriers: encouraging teacher use of feedback resources. A report from the teacher Feedback Resources Project. Learning Forward.

Paavola, S., Engeström, R., & Hakkarainen, K. (2012). The trialogical approach as a new form of mediation. In A. Moen, A. I. Mørch, & S. Paavola (Eds.), Collaborative Knowledge Creation (pp. 1–14). SensePublishers. https://doi.org/10.1007/978-94-6209-004-0_1

Prestigiacomo, R., Hunter, J., Knight, S., Martinez-Maldonado, R., & Lockyer, L. (2020). Data in practice: a participatory approach to understanding pre-service teachers’ perspectives. Australasian Journal of Educational Technology, 36(6), 107–119. https://doi.org/10.14742/ajet.6388.CrossRef

Reeve, J., & Tseng, C. M. (2011). Agency as a fourth aspect of students’ engagement during learning activities. Contemporary Educational Psychology, 36(4), 257–267. https://doi.org/10.1016/j.cedpsych.2011.05.002.CrossRef

Schildkamp, K., Karbautzki, L., & Vanhoof, J. (2014). Exploring data use practices around Europe: Identifying enablers and barriers. Studies in Educational Evaluation, 42, 15–24. https://doi.org/10.1016/j.stueduc.2013.10.007

Schildkamp, K., & Kuiper, W. (2010). Data-informed curriculum reform: which data, what purposes, and promoting and hindering factors. Teaching and Teacher Education, 26(3), 482–496. https://doi.org/10.1016/j.tate.2009.06.007.CrossRef

Schildkamp, K., Smit, M., & Blossing, U. (2019). Professional Development in the Use of Data: From Data to Knowledge in Data Teams.Scandinavian Journal of Educational Research, 63(3),393–411. https://doi.org/10.1080/00313831.2017.1376350

Schwendimann, B. A., Rodríguez-Triana, M. J., Vozniuk, A., Prieto, L. P., Boroujeni, M. S., Holzer, A., Gillet, D., & Dillenbourg, P. (2017). Perceiving learning at a glance: a systematic literature review of learning Dashboard Research. IEEE Transactions on Learning Technologies, 10(1), 30–41. https://doi.org/10.1109/TLT.2016.2599522.CrossRef

Sergis, S., & Sampson, D. (2017). Teaching and learning analytics to support Teacher Inquiry: a systematic literature review. In A. Peña-Ayala (Ed.), Learning analytics: fundaments, applications, and trends (pp. 25–63). Springer.

Skinner, E., Furrer, C., Marchand, G., & Kindermann, T. (2008). Engagement and disaffection in the classroom: part of a larger motivational dynamic? Journal of Educational Psychology, 100(4), 765–781. https://doi.org/10.1037/a0012840.CrossRef

Vermunt, J. D., Vrikki, M., van Halem, N., Warwick, P., & Mercer, N. (2019). The impact of lesson study professional development on the quality of teacher learning. Teaching and Teacher Education, 81, 61–73. https://doi.org/10.1016/j.tate.2019.02.009.CrossRef

Wang, F., & Hannafin, M. J. (2005). Design-based research and technology-enhanced learning environments. Educational Technology Research and Development, 53(4), 5–23. https://doi.org/10.1007/BF02504682.CrossRef

Wayman, J. C., Cho, V., Jimerson, J. B., & Spikes, D. D. (2012). District-wide Effects on Data Use in the Classroom. Education Policy Analysis Archives, 20(25), 1–28. https://doi.org/10.14507/epaa.v20n25.2012.CrossRef

Wayman, J. C., Cho, V., Mandinach, E., Supovitz, J., & Wilkerson, S. (2016). Guide to using the Teacher Data Use Survey.U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance, Regional Educational Laboratory Appalachia.

Wise, A. F., & Jung, Y. (2019). Teaching with analytics: towards a situated model of instructional decision-making. Journal of Learning Analytics, 6(2), 53–69. https://doi.org/10.18608/jla.2019.62.4.CrossRef

Wise, A. F., & Shaffer, D. W. (2015). Why theory matters more than ever in the age of big data. Journal of Learning Analytics, 2(2), 5–13. https://doi.org/10.18608/jla.2015.22.2.CrossRef

Wolters, C. A. (2004). Advancing achievement goal theory: using goal structures and goal orientations to predict students’ motivation, cognition, and achievement. Journal of Educational Psychology, 96(2), 236–250. https://doi.org/10.1037/0022-0663.96.2.236.CrossRef

Title: Mediating Teacher Professional Learning with a Learning Analytics Dashboard and Training Intervention
Authors: Manisha Khulbe
Kairit Tammets
Publication date: 23-02-2023
Publisher: Springer Netherlands
Published in: Technology, Knowledge and Learning / Issue 3/2023
Print ISSN: 2211-1662
Electronic ISSN: 2211-1670
DOI: https://doi.org/10.1007/s10758-023-09642-0

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Other articles of this Issue 3/2023

Developing the Teacher Self-Efficacy Scale in the Use of ICT at Home for Pre-school Distance Education During Covid-19

Female Students in Quantitative Courses: An Exploration of their Motivational Sources, Learning Strategies, Learning Behaviors, and Course Achievement

Affective State Analysis During Online Learning Based on Learning Behavior Data

Design Elements of Conflict: A Design Study of a Gamified Smartphone Application for Employee Onboarding

Pre-service Teachers’ Reflections on Attitudes Towards Teaching and Learning Mathematics with Online Platforms at School: A Case Study in the Context of a University Online Training

Performance, Participation and Perception of Computer Education Students Toward Flipped Learning

Premium Partners