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Introduction: Media comparison studies examining the effectiveness of immersive virtual reality in education have yielded inconclusive findings, leaving the question of its impact on learning compared to conventional media unanswered. To address this issue, our study employs a novel approach that combines media comparison with an investigation on the influence of broader educational context. Methods: In the experiment, 262 students from two distinct types of lower secondary schools—comprehensive school and multi‐year gymnasium (a selective academic school)—participated. The students received a lesson on topography and contour line interpretation, using either an immersive virtual environment or a PowerPoint slideshow. A transfer test was carried out before, immediately after, and 1 month after the lesson to measure knowledge application. Results: The impact of the media (immersive virtual reality vs. PowerPoint slideshow) on learning outcomes was found to be minimal, with no clear advantage of one over the other in any experimental condition. In contrast, a significant influence on learning gains was observed due to school type. Multi‐year gymnasium students consistently outperformed comprehensive school students in the pre‐test and demonstrated greater learning gains, regardless of the learning media. Conclusion: The present study employs an innovative approach by integrating a comparative analysis of different media types with an investigation into the impact of learner characteristics. By including students from distinct types of schools, the study provides insights into the differential effects of immersive virtual reality in varied educational contexts. Lay Description: What is already known about this topic: Media comparison studies typically assess the effectiveness of immersive virtual reality as a learning medium in comparison to other instructional methods in education.The findings of these studies differ markedly.Numerous factors impact learning outcomes in an immersive virtual environment. What this paper adds: Recommendation that research in the field should explore not only if but also when and how IVR learning is effective.Evidence that learning achievements may not be affected by the medium used.Evidence that the type of school can significantly influence learning gains.Evidence that cognitive dispositions, such as spatial abilities, can be another factor that influence learning outcomes. Implications for practice: A technology‐centred approach alone does not allow for a proper evaluation of the learning gain potential of IVR, learner characteristics and broader educational context should also be taken into account.IVR as a learning medium may not be appropriate for all students and every educational setting.To ensure reliable evaluation of learning gains, it is necessary to align the content and format of the intervention in both learning mediums as closely as possible.Measuring learning gains not only immediately after the intervention but also with a significant time delay can contribute to a more comprehensive understanding. [ABSTRACT FROM AUTHOR]

Background: The coronavirus pandemic has affected education worldwide. Estonian schools moved to distance learning on March 16. Objectives: This paper outlines the stages of unexpected and temporary changes affecting different stakeholders based on activity and content of the messages in the Facebook group 'Homeschooling with technology'. Also the applicability of the concerns‐based adoption model was explored to explain these changes. Methods: The investigated timespan includes the week before the emergency situation and the weeks of the school term and school holidays during the emergency situation, with 52 days in total, divided into seven periods. The 872 messages were coded by two researchers and changes were examined. Results and Conclusions: Four stages were identified, from low exposure and involvement with the change to focusing on collaboration and skipping the consequence stage. Furthermore, the new changes in the educational system might focus people again on personal concerns. Implications: The results help capture the changes in teaching and learning situation caused by the coronavirus pandemic in order to learn from these changes and be prepared for such situations in the future. Lay Description: What is already known about this topicIn the emergency situation, even well‐experienced teachers were not sure what and how to teach.There are several models and there are different models on handling the changes in education.Concerns‐based adoption model (CBAM) looks at how change affects people.Emotions have changed from negative to neutral in social media during school closures What this paper addsPrevious studies have been based mostly on surveys, but this paper adds an in‐depth analysis of messages from social media.Four stages describing how changes affect people have identified.New changes brought back personal concerns and no impact concerns raised.CBAM model is applicable in explaining unexpected temporary changes Implications for practice and/or policyIn teacher training, curricula courses about distance learning methodologies and tools should be added.National guidelines about the management of distance learning situations should be prepared. [ABSTRACT FROM AUTHOR]

Background: There is a lack of critical or empirical work interrogating the nature and purpose of evaluating technology use in education. Objectives: In this study, we examine the values underpinning the evaluation of technology use in education through field specialist perceptions. The study also poses critical reflections about the rigour of evaluation instruments development in the educational technology field. Method: A total of 48 domain specialists were surveyed to investigate the face and content validity of 39 items under eight constructs, with both qualitative and quantitative data from the survey analysed. Results: There was an alignment between the constructs that the specialists felt were important and the constructs that have typically been the focus of empirical studies, with field specialists indicating high relevance scores for technology (M = 3.24/4), learning outcomes (M = 3.20/4), affective elements (M = 3.19/4), behaviour (M = 3.15/4), presence/community (M = 3.07/4), teaching/pedagogy (M = 3.01/4), design (M = 2.96/4), and institutional environment (M = 2.86/4). Only a minority of other studies were found to perform face and content validity checks and even then only with small samples of respondents (usually n ≤ 5). Implications: Specialists in educational technology research confirm that all eight dimensions are important to consider when evaluating the use of technology in education. Thorough face and content validity processes should be adopted when developing educational technology evaluation instruments. Further work has validated an eight factor 28 item instrument for evaluating the use of technology in education using a large sample of students from a global open learning online course. Lay Description: What is already known about this topic: Comprehensive evaluation of technology use is essential to make decisions on learning technology strategies.There is a lack of critical work interrogating how technology use is evaluated in education.There is a need for developing evaluation instruments in the educational technology field. What this paper adds: An examination of 48 field specialist perceptions of important constructs when evaluating technology use in education.Field specialists agreed that eight constructs identified in empirical studies were relevant to educational technology evaluation.Evidence of limited face and content validation processes based on previous empirical work.A comprehensive 39‐item instrument for evaluating technology use in education. Implications of study findings for practitioners: Adopt a broad range of constructs when evaluating the use of technology in education.Apply face and content validation processes involving a large sample of experts.Consider using the 39‐item instrument to evaluate educational technology use. [ABSTRACT FROM AUTHOR]

Emotions are critical to learning. However, the function of emotions in the emerging context of massive open online courses (MOOCs) has been under‐researched. The present study complemented this line of research by modelling the relation between learner emotions, engagement with videos, engagement with assignments, and self‐perceived achievement in a small private online course—a localized instance of an extended MOOC. The results suggested that whereas enjoyment, excitement, boredom, and annoyance were all significant predictors of video engagement, only excitement and annoyance were significant predictors of assignment engagement. Excitement, in particular, was the strongest or stronger predictor of both types of engagement. In addition, both types of engagement predicted self‐perceived achievement, but video engagement predicted self‐perceived achievement via the mediation of assignment engagement. Implications for designing more effective MOOCs were proposed. Lay Description: What is currently known about the subject Emotions predict engagement in learning settings other than MOOCs.Engagement predicts achievement in learning settings including MOOCs.Assignment engagement predicts achievement in MOOCs better than video engagement. What this paper adds The two types of engagement are predicted by different sets of emotions.Engagement predicts self‐perceived achievement in the SPOC.Video engagement predicts self‐perceived achievement via the mediation of assignment engagement.The majority of systematic reviews did not evaluate the quality of the primary papers which they examined. Implications for practitioners MOOC researchers should pay more attention to the design of assignments.MOOC developers should try to build more emotionally‐sound courses and platforms. [ABSTRACT FROM AUTHOR]

Abstract: The aim of this paper is to provide insights into differences between pre‐service teachers based on the areas of technological pedagogical content knowledge (TPACK) and the areas of theory of planned behaviour (TPB) in the context of using information and communication technology in education. The target group consisted of 267 first‐year pre‐service teachers at 3 Finnish universities. Differences between pre‐service teachers were outlined using cluster analysis based on their knowledge of different TPACK areas (the respondents' weak and strong areas). To see how the TPB areas aligned with the 4 TPACK clusters, 1‐way analysis of variance was used. Statistically significant differences between the 4 clusters were found in all the TPB areas except subjective norms. These results provide insights into the differences among pre‐service teachers in the context of TPACK and the TPB. They also suggest that instead of considering pre‐service teachers as one homogenous group, we need to understand the variations among their abilities and knowledge in order to be able to provide them with support they need within teacher education. [ABSTRACT FROM AUTHOR]