Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 1 |
| Since 2017 (last 10 years) | 2 |
| Since 2007 (last 20 years) | 3 |
Descriptor
Source
| Educational Technology… | 3 |
Author
Publication Type
| Journal Articles | 3 |
| Reports - Research | 2 |
| Reports - Evaluative | 1 |
Education Level
| Higher Education | 1 |
| Postsecondary Education | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Kasani, Hamed Abbasi; Mourkani, Gholamreza Shams; Seraji, Farhad; RezaeiZadeh, Morteza; Aghazadeh, Solmaz; Abedi, Hojjat – Educational Technology Research and Development, 2023
The purpose of this study was to develop and measure the usability of the software prototype of formative assessment in the LMS. This study was applied in terms of research objective and mixed method (qualitative-quantitative) in terms of data collection in which an exploratory sequential mixed methods design was used. In addition, in order to…
Descriptors: Computer Software, Formative Evaluation, Usability, Design
Improving Workplace-Based Assessment and Feedback by an E-Portfolio Enhanced with Learning Analytics
van der Schaaf, Marieke; Donkers, Jeroen; Slof, Bert; Moonen-van Loon, Joyce; van Tartwijk, Jan; Driessen, Eric; Badii, Atta; Serban, Ovidiu; Ten Cate, Olle – Educational Technology Research and Development, 2017
Electronic portfolios (E-portfolios) are crucial means for workplace-based assessment and feedback. Although E-portfolios provide a useful approach to view each learner's progress, so far options for personalized feedback and potential data about a learner's performances at the workplace often remain unexploited. This paper advocates that…
Descriptors: Personnel Evaluation, Evaluation Methods, Feedback (Response), Electronic Publishing
Scholes, Vanessa – Educational Technology Research and Development, 2016
There are good reasons for higher education institutions to use learning analytics to risk-screen students. Institutions can use learning analytics to better predict which students are at greater risk of dropping out or failing, and use the statistics to treat "risky" students differently. This paper analyses this practice using…
Descriptors: Data Collection, Data Analysis, Educational Research, At Risk Students

Peer reviewed
Direct link
