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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). Lay Description: What is currently known about the subject matter: Accounting for student expectations allows for a service that is meaningful.SELAQ measures student expectations towards Learning Analytics services.The 12 items of the SELAQ can be explained by a two‐factor structure (Ethical and Privacy Expectations and Service Feature Expectations). What their paper adds to this: Validation of the SELAQ in three contextsA discussion of localized sources of strainAn assessment of measurement quality in each contextA general comparison of student expectations across contexts The implications of study findings for practitioners: SELAQ can be used with Spanish and Dutch students.SELAQ responses provide a much needed input from end‐users in Learning Analytics implementations. [ABSTRACT FROM AUTHOR]

Aims To report a systematic review of the psychometric properties of self-report instruments to identify the symptoms of anxiety in pregnancy to help clinicians and researchers select the most suitable instrument. Background Excessive anxiety in pregnancy is associated with adverse birth outcomes, developmental and behavioural problems in infants and postnatal depression. Despite recommendations for routine psychological assessment in pregnancy, the optimal methods to identify anxiety in pregnancy have not been confirmed. Design Psychometric systematic review. Data sources A systematic literature search of the multiple databases (1990-September 2014). Review methods Identification of self-report instruments to measure anxiety in pregnancy using COSMIN guidelines to assess studies reporting a psychometric evaluation of validity and reliability. Results Thirty-two studies were included. Studies took place in the UK, Australia, Belgium, Canada, Germany, Italy, Scandinavia, Spain and the Netherlands. Seventeen different instruments were identified. Measures of validity were reported in 19 papers and reliability in 16. The overall quality of the papers was rated as fair to excellent using the COSMIN checklist. Only one paper scored excellent in more than one category. Conclusion Many instruments have been adapted for use in different populations to those for which they were designed. The State Trait Anxiety Inventory, Edinburgh Postnatal Depression Scale and the Hospital Anxiety and Depression Scale have been tested more frequently than other instruments, yet require further assessment to confirm their value for use in pregnancy. [ABSTRACT FROM AUTHOR]