From data to actions: Instructors' decision making based on learners' data in online emergency remote teaching

Maya Usher, Arnon Hershkovitz, Alona Forkosh-Baruch

Research output: Contribution to journalArticlepeer-review

Abstract

The outbreak of the COVID-19 pandemic has changed education dramatically, with the sudden shift from face-to-face to emergency remote teaching. Online learning environments may facilitate data-driven instructional process; yet, our understanding regarding data-driven decisions is still limited. This quantitative study examined types of learners' data that higher education instructors have access to, are interested in, and decisions they would consider making upon exposure to, while comparing emergency remote teaching with traditional teaching. Data were collected via an online questionnaire distributed among higher education instructors during the first COVID-19 outbreak (N = 195, affiliated with 108 different academic institutions in 35 countries). Instructors were requested to refer to a face-to-face course that was shifted under these emergency circumstances to online teaching. Findings indicated a broader access to learners' data while teaching the course face-to-face and a slightly greater interest in learners' data while teaching the course in an emergency remote teaching mode. These complimentary findings depict a situation in which instructors lack face-to-face cues about their students without accessing alternative sources of data. Moreover, when teaching online versus face-to-face, instructors showed more interest and higher intention to make decisions based on data about learners' collaborative learning and social and emotional support, which highlights instructors' interest in aspects of learning that are less visible during online teaching. Practitioner notes What is already known about this topic Evidence regarding the vital role of the instructor in online courses. Online learning environments collect digital traces of learners. Learners' data may assist in the improvement of teaching by implementing data-driven decision making. Evidence that the COVID-19 pandemic revealed a major liability in preparation and training for online teaching. The understanding of instructors' perspectives regarding the process of data-driven decisions, especially in times of ERT, is still limited. What this paper adds We highlight instructors' perceived access to, interest in, and willingness to make decisions based on learners' data. We take a within-subject approach for determining instructors' perceptions of learners' data during ERT compared with face-to-face teaching. We bring evidence to instructors' lesser access to (despite learners' digital traces), and greater interest in, learners' data during ERT. We bring evidence to instructors' higher inclination towards making data-driven decisions during ERT, due to lack of F2F evidence. We bring evidence to a strong correlation between instructors' interest in learners' data and willingness to make data-driven decisions. Implications for practice and/or policy Instructors should be trained for socio-emotional support for students in times of ERT. Higher education institutions should collect data on learners' socio-emotional status in times of ERT. Policies of data collection in educational institutions should be formed jointly with instructors. Hectic times of ERT force higher education policymakers to rethink their academic paradigm regarding online as well as F2F pedagogical practices.

Original languageEnglish
Pages (from-to)1338-1356
Number of pages19
JournalBritish Journal of Educational Technology
Volume52
Issue number4
DOIs
StatePublished - Jul 2021

Keywords

  • data-driven decision-making
  • emergency remote teaching
  • higher education
  • instructor perspective
  • online teaching

All Science Journal Classification (ASJC) codes

  • Education

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