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Instructional Usability and Learner-User eXperience Assessment in a Virtual Reality Educational Milieu: A Deductive Tech-Instructionality Model from EdTech
2023 Future of Educational Innovation-Workshop Series Data in Action, FEIWS 2023 ; 2023.
Article in English | Scopus | ID: covidwho-2321740
ABSTRACT
Educational Technology (EdTech) lacks a foundational, formal, scientific, epistemic theory. Therefore, it lacks native constructs/variables and an epistemological object of study for scientifically deploying its work. This study determines the existence (ontology) of the theorized constructs Instructional Usability (UsI) and Learner-User eXperience (LUX) and defines their characterization (epistemology). Both constructs were modeled and instrumented. Furthermore, a Tech-Instructionality Model (TIM) was theorized and developed in this paper, both analytically and empirically. The model integrates UsI and LUX as two pairs of constructs linked with two EdTech epistemological objects of study, the instructional interface and the instructional interaction in two assessment modalities, testing mode (user-learner view) and inspection mode (expert/designer view). Two instruments were developed and validated in this study for testing mode, the Instructional Usability Scale (SUsI) and the Learner-User eXperience Questionnaire (QLUX). Both instruments were tested in a non-immersive virtual reality educational milieu during the academic lockdown of the Covid19 pandemic. The results show that both SUsI and QLUX consistently measured UsI and LUX, thus, providing a valid assessment for tech-instructionality and a foundation for constructing a scientific theory of EdTech. © 2023 IEEE.
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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Observational study / Prognostic study Language: English Journal: 2023 Future of Educational Innovation-Workshop Series Data in Action, FEIWS 2023 Year: 2023 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Observational study / Prognostic study Language: English Journal: 2023 Future of Educational Innovation-Workshop Series Data in Action, FEIWS 2023 Year: 2023 Document Type: Article