27 SES 13 B, Language and Education Research
Learning analytics can make teaching and learning more efficient. Learning analytics can be defined as “the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs”(Siemens & Gasevic, 2012). Data from online tests not only provide feedback for the learners, but inform teachers as well about both the performance level and details of the test performance of their students. Teachers might use these insights in the preparation of their lessons and teaching in class. However, most research on learning analytics has been done in the domain of higher education and on data generated from online learning environments. Moreover, a large body of research has focused on supporting students with tools that enhance students’ awareness of their activities in, for example, collaborative learning (cf., Dehler, Bodemer, Buder, & Hesse, 2011; Jermann, Soller, & Muehlenbrock, 2005). Yet learning analytics can inform teachers in similar ways (cf. Van Leeuwen, Janssen, Erkens, & Brekelmans, 2014) and can also make off-line teaching and learning more efficient, in which teachers adapt their pedagogy on the basis of online test performances of their students.
Formative feedback or assessment for learning seems to be a crucial concept here. Assessment for learning can be defined as follows. “Practice in a classroom is formative to the extent that evidence about student achievement is elicited, interpreted, and used by teachers, learners, or their peers, to make decisions about the next steps in instruction that are likely to be better, or better founded, that the decisions they would have taken in the absence of the evidence that was elicited” (Black & William, 2009. p.9). In assessment for learning, feedback includes not only information about the gap between the actual level and the reference level, it also includes information generated within a particular system and for a particular purpose, making feedback necessarily domain specific (William, 2011). Generally, literature suggests that the use of assessment to inform instruction might have significant impact on learning, with two features which appear to be important in designing assessment that will support learning (William, 2007, 2011). First, the evidence should be more than information about the gap between current and desired performance; it must also provide information about what kinds of instructional activities are likely to result in improving performance. Second, learners should be engaged in actions to improve learning, which might be remedial activities by the teacher, peer support or reflecting on different ways to move their learning forward.
In the current study, a case study has been carried out with five secondary language teachers using online performance data of their students to adapt their lesson plans and teaching in the next lessons. Three research questions were formulated:
- What kind of learner data do teachers use for their teaching practice?
- How do teachers use learner data in their instructional practice?
- How are these classroom instructions evaluated by students?
Black, P. J., & William, D. (2009). Developing the theory of formative assessment. Educational Assessment, Evaluation and Accountability, 21(1) 5-31. Dehler, J., Bodemer, D., Buder, J., Hesse, F. W. (2011). Guiding knowledge communication in CSCL via group knowledge awareness. Computers in Human Behavior, 27(3), 1068-1078. Jermann, P., Soller, A., & Muehlenbrock, M. (2005). From mirroring to guiding: a review of state of the art technology for supporting collaborative learning. International Journal of Artificial Intelligence in Education, 15(4), 261-290. Leeuwen, A. van, Janssen, J., Erkens, G., & Brekelmans, M. (2014). Supporting teachers in guiding collaborating students: effects of learning analytics in CSCL. Computers & Education, 79(1), 28-39. Siemens, G., & Gasevic, D. (2012). Guest editorial- learning and knowledge analytics. Educational Technology & Society, 15(3), 1-2. Wiliam, D. (2007). Keeping learning on track: Classroom assessment and the regulation of learning. In F. K. Lester, Jr., (Ed.). Second handbook of mathematics teaching and learning (pp. 1053–1098). Greenwich, CT: Information Age Publishing. William, D. (2011). What is assessment for learning? Studies in Educational Evaluation, 37(1), 3-14.
00. Central Events (Keynotes, EERA-Panel, EERJ Round Table, Invited Sessions)
Network 1. Continuing Professional Development: Learning for Individuals, Leaders, and Organisations
Network 2. Vocational Education and Training (VETNET)
Network 3. Curriculum Innovation
Network 4. Inclusive Education
Network 5. Children and Youth at Risk and Urban Education
Network 6. Open Learning: Media, Environments and Cultures
Network 7. Social Justice and Intercultural Education
Network 8. Research on Health Education
Network 9. Assessment, Evaluation, Testing and Measurement
Network 10. Teacher Education Research
Network 11. Educational Effectiveness and Quality Assurance
Network 12. LISnet - Library and Information Science Network
Network 13. Philosophy of Education
Network 14. Communities, Families and Schooling in Educational Research
Network 15. Research Partnerships in Education
Network 16. ICT in Education and Training
Network 17. Histories of Education
Network 18. Research in Sport Pedagogy
Network 19. Ethnography
Network 20. Research in Innovative Intercultural Learning Environments
Network 22. Research in Higher Education
Network 23. Policy Studies and Politics of Education
Network 24. Mathematics Education Research
Network 25. Research on Children's Rights in Education
Network 26. Educational Leadership
Network 27. Didactics – Learning and Teaching
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