TY - JOUR
T1 - Assessing the validity of a learning analytics expectation instrument
T2 - A multinational study
AU - Whitelock‐Wainwright, Alex
AU - Gasevic, Dragan
AU - Tsai, Yi-Shan
AU - Drachsler, H.J.
AU - Scheffel, M.
AU - Muñoz-Merino, Pedro J.
AU - Tammets, Kairit
AU - Delgado Kloos, Carlos
N1 - Whitelock‐Wainwright, A, Gašević, D, Tsai, Y‐S, Drachsler H., Scheffel, M., Muñoz‐Merino, P. J., Tammets, K., Delgado Kloos, C. (2020). Assessing the validity of a learning analytics expectation instrument: A multinational study. J Comput Assist Learn. 2020; 1– 32. https://doi.org/10.1111/jcal.12401.
PY - 2020/4
Y1 - 2020/4
N2 - To assist higher education institutions in meeting the challenge of limited student engagement in the implementation of Learning Analytics services, the Questionnaire for Student Expectations of Learning Analytics (SELAQ) was developed. This instrument contains 12 items, which are explained by a purported two-factor structure of “Ethical and Privacy Expectations” and “Service Feature Expectations.” As it stands, however, the SELAQ has only been validated with students from UK university, which is problematic on account of the interest in Learning Analytics extending beyond this context. Thus, the aim of the current work was to assess whether the translated SELAQ can be validated in three contexts (an Estonian, a Spanish, and a Dutch University). The findings show that the model provided acceptable fits in both the Spanish and Dutch samples, but was not supported in the Estonian student sample. In addition, an assessment of local fit is undertaken for each sample, which provides important points that need to be considered in future work. Finally, a general comparison of expectations across contexts is undertaken, which are discussed in relation to the General Data Protection Regulation (2018).
AB - To assist higher education institutions in meeting the challenge of limited student engagement in the implementation of Learning Analytics services, the Questionnaire for Student Expectations of Learning Analytics (SELAQ) was developed. This instrument contains 12 items, which are explained by a purported two-factor structure of “Ethical and Privacy Expectations” and “Service Feature Expectations.” As it stands, however, the SELAQ has only been validated with students from UK university, which is problematic on account of the interest in Learning Analytics extending beyond this context. Thus, the aim of the current work was to assess whether the translated SELAQ can be validated in three contexts (an Estonian, a Spanish, and a Dutch University). The findings show that the model provided acceptable fits in both the Spanish and Dutch samples, but was not supported in the Estonian student sample. In addition, an assessment of local fit is undertaken for each sample, which provides important points that need to be considered in future work. Finally, a general comparison of expectations across contexts is undertaken, which are discussed in relation to the General Data Protection Regulation (2018).
KW - COVARIANCE STRUCTURE-ANALYSIS
KW - PRINCIPLES
KW - STRUCTURAL EQUATION MODELS
KW - STUDENT PERCEPTIONS
KW - SUPPORT
KW - Student expectations
KW - learning analytics
KW - multinational
KW - questionnaire
U2 - 10.1111/jcal.12401
DO - 10.1111/jcal.12401
M3 - Article
SN - 0266-4909
VL - 36
SP - 209
EP - 240
JO - Journal of Computer Assisted Learning
JF - Journal of Computer Assisted Learning
IS - 2
ER -