Exploring the specification of educational compatibility of virtual reality within a technology acceptance model

This study investigated the specification of educational compatibility within a technology acceptance model (TAM) suited to engaging educational technologies. Attitudes towards virtual reality (VR) for learning was used to test the experimental model. One hundred and seventy-nine valid survey responses were collected from 517 potential participants with the majority from first-year university students. The independent variables were educational compatibility, cognitive engagement, social influence, system attributes, perceived anxiety and facilitating conditions. Exploratory factor analysis showed that educational compatibility and attitude were collinear, and therefore were combined into one construct. Confirmatory factor analysis indicated that the combined educational compatibility-attitude construct and perceived usefulness were not discriminant. Two structural models were therefore compared: one where educational compatibility-attitude items were incorporated within perceived usefulness, and another where educational compatibility-attitude items were excluded entirely. The results showed that incorporating educational compatibility-attitude items within perceived usefulness affected the influence of cognitive engagement and system attributes on perceived usefulness, though overall model power was unchanged. The results suggested that (a) educational compatibility and attitude could be redundant, and (b) incorporating educational compatibility into perceived usefulness may help specify educationally focused TAMs. Implications for practice or policy: Researchers may regard educational compatibility and attitude to be redundant and exclude them from TAMs as separate constructs. Researchers could consider tailoring the perceived usefulness construct to make it more specific to the educational context, for example by including one or more educational compatibility items.

Challenges in a mobile English telecollaborative project: Towards a conceptual model

This paper, drawing upon a mobile telecollaborative project, resonates with the rapid development of technology in language learning. We employed the instant messaging app WeChat to create an English telecollaborative environment for two groups of Chinese students to communicate within. Interview data were triangulated with students’ chat transcripts and comments from a teacher’s reflective journal. A mixed-methods approach, including quantitative descriptive analysis, thematic analysis and content analysis, was used to investigate the challenges and the linguistic performance by applying the community of inquiry framework to the students’ chats. The analysis illustrates some of the complexities and challenges of using online apps as a way of communicating in a second language: students expected more teacher support, they struggled to use the app due to their physical environments and they felt that they were not sufficiently well prepared for chatting in an English medium environment. Based on the findings, a conceptual model is proposed for consideration when encouraging students to engage in telecollaborative learning. Implications for practice or policy: Teachers should enhance their visibility in mobile telecollaborative projects by promoting participants’ contribution through different facilitation techniques. Teachers and educators can capitalise on the proposed conceptual model to guide their own design of such online learning experiences for their learners. Telecollaborative learning can be improved by taking into account various factors such as physical environment, the medium of communication and the potential incentives.

Leveraging asynchronous speaking tasks to promote willingness and confidence to speak in Spanish: A qualitative study

This study describes the experiences of students in a flipped intermediate Spanish college class who used a video discussion digital tool to develop their confidence to speak in the foreign language. Students participated in a series of 10 speaking tasks designed based on the framework on technology-mediated tasks (Gonzalez-Lloret & Ortega, 2014) and the world-readiness standards for communicative performance of the American Council on the Teaching of Foreign Languages (2015). Through semi-structured interviews and reflection journals, students shared their learning accomplishments, unveiled their inner fears in speaking skills and detailed their journey in gaining confidence to speak in Spanish. Their experiences showed that willingness to communicate and self-efficacy are driving forces that, fostered in a brave learning environment, enable students to take risks and be creative with the language. The study also presents pedagogical implications regarding the design of technology-mediated tasks and the conditions of the learning environment that can foster or hinder students’ language oral communicative skills. Implications for practice or policy: Technology-mediated tasks should be designed based on a learner-centred approach and the affordances of the tool to promote communicative competence in foreign and second language learning. Technology-mediated tasks can promote the development of confidence to use the foreign and second language more spontaneously, while allowing students to fail without being judged or penalised. Technology-mediated tasks can give students some control over their own learning process, facilitating opportunities for self-monitoring to gain confidence in speaking in the foreign or second language.

The role of change in AJET in 2021: reflections, bibliometrics, and future plans

The end of 2021 marks the first anniversary of the new AJET Lead Editor Team. In this editorial we explore the role of change in the past two years of educational technology in tertiary education, and what this has meant for AJET. We also present the bibliometrics for the year, a summary of what was published in AJET in 2021, and what we have learnt as the new lead editor team. We conclude with a look at what is next for AJET as we move into 2022 and a thank you to all the important people who make AJET a success.

Active learning in history teaching in higher education: The effect of inquiry-based learning and a student response system-based formative assessment in teacher training

Information and communication technology has produced changes in the demands of modern-day society (e.g., most jobs will require advanced digital skills in the short term). In addition, nowadays, new active methodologies using emerging technologies are being put into practice. However, little research has been conducted with pre-service teachers, particularly in the teaching of history. This quantitative study analysed the impact of the implementation of a mixed methodology using inquiry-based learning and a student response system (SRS) for the formative assessment of the academic achievement of 240 prospective primary teachers of history. The application of this mixed methodology shows better academic results than traditional lecture-based teaching. In addition, students’ scores achieved through use of the SRS predicted the scores of male students in the final exam; however, this was not in the case for females. Implications for practice or policy: The introduction of information and communication technology into history teaching brings active learning environments in higher education. Pre-service teachers can improve their knowledge of history through the implementation of inquiry-based learning methodology and SRSs. Our results indicate that an SRS can be an effective tool for teachers to carry out students' formative assessment. Teachers can effectively use SRS scores to predict male students' performance in history, but not female performance.

Collaborative programming problem-solving in augmented reality: Multimodal analysis of effectiveness and group collaboration

Although numerous studies have demonstrated different ways that augmented reality (AR) can assist students to understand the learning content via contextualised visualisation, less explored is its effect on collaborative problem-solving (CPS) in computer programming. This study aims to investigate how AR affects a CPS in a programming task. We designed a mobile app that could visualise computer programming in AR and non-AR 3D images. The app could involve two participants working together on a programming problem face to face in the same workspace. We conducted a within-subjects experiment to compare their AR experience to the non-AR experience and collected multimodal usage data about the task performance, verbal communication, and user experience. The analysis showed that the participants in the AR experience had higher task performance and more insightful communication than the non-AR. The participants also had positive attitudes toward the use of AR in classroom instructions. In a semi-structured interview, the participants reflected that AR helped them engage in the content and analyse the task easier. Based on this study, we discuss several challenges and implications for future instruction designers. Implications for practice or policy: AR can improve student engagement in a collaborative problem-solving task. AR has the potential to promote and improve group communication in collaborative work. Instruction designers may need to carefully align the characteristics of AR with the task content especially when physical models are rarely used in the learning content.

Physical therapy using robotics: A project-based learning experience for undergraduate students

The dynamic society we live in requires constant adaptation and innovation on every aspect of our daily lives, allowing us to improve the necessities of different people by doing it. For this study, we used a new approach with project-based learning to go beyond the typical environment in higher education and bring solutions to real-life scenarios. The project was developed with undergraduate engineering students in collaboration with a rehabilitation institute in Mexico City to design a physical therapy routine using the NAO robot. It allowed interaction between young patients in real time and fostered empathy while developing a final usable product. The study measured the usability of the robotic platform during the rehabilitation sessions and the reproducibility of the project through Cronbach's alpha evaluation. The usability results show a higher interest in the project from both the patients and the medical staff involved while constructing the material needed to develop a product that matches the standards given by the rehabilitation institute. Implications for practice or policy: Therapists could change traditional approaches to caregiving while adopting new technological methodologies using robots. Higher education students could supplement their school curricula with real-case scenarios such as creating innovative therapy sessions for people with physical disabilities. Schools might need to collaborate with a wide range of institutions to provide technological solutions to real problems.

Students’ experiences and acceptance of emergency online learning due to COVID-19

At the outbreak of the COVID-19 pandemic, higher education institutions around the world were compelled to bring forth suitable alternatives to secure continuity in the process of education. To gather data that would indicate the quality and efficiency of online teaching in higher education in south and south-eastern Serbia initiated at the outbreak of the pandemic and the state of emergency declared in March 2020, we conducted a research study to provide the necessary information from students attending undergraduate academic studies. The research was conducted in two phases. The first phase consisted of quantitative research conducted on a sample of 211 students. The data collected were processed by resorting to factor analysis to determine specific factors as a starting point for designing questions for the second research phase. The second phase was implemented by conducting semi-structured interviews on a sample of 61 students. The main intention was to determine key characteristics of the teaching process realised in the context of an emergency transition to the form of teaching which had not been prepared or resorted to beforehand. We identified certain specifics in this regard, as a starting point for improving existing practice. Implications for practice or policy: It is necessary to secure a suitable level of institutional support, to maintain the quality of higher education in unforeseen social circumstances. It is necessary to adequately prepare for and support teachers and students in online teaching at both institutional and national level. To avoid adverse effects on individual students in the circumstances of online teaching, it is necessary to meet students´ educational, social and emotional needs.

Applying natural language processing to automatically assess student conceptual understanding from textual responses

In this study, we applied natural language processing (NLP) techniques, within an educational environment, to evaluate their usefulness for automated assessment of students’ conceptual understanding from their short answer responses. Assessing understanding provides insight into and feedback on students’ conceptual understanding, which is often overlooked in automated grading. Students and educators benefit from automated formative assessment, especially in online education and large cohorts, by providing insights into conceptual understanding as and when required. We selected the ELECTRA-small, RoBERTa-base, XLNet-base and ALBERT-base-v2 NLP machine learning models to determine the free-text validity of students’ justification and the level of confidence in their responses. These two pieces of information provide key insights into students’ conceptual understanding and the nature of their understanding. We developed a free-text validity ensemble using high performance NLP models to assess the validity of students’ justification with accuracies ranging from 91.46% to 98.66%. In addition, we proposed a general, non-question-specific confidence-in-response model that can categorise a response as high or low confidence with accuracies ranging from 93.07% to 99.46%. With the strong performance of these models being applicable to small data sets, there is a great opportunity for educators to implement these techniques within their own classes. Implications for practice or policy: Students’ conceptual understanding can be accurately and automatically extracted from their short answer responses using NLP to assess the level and nature of their understanding. Educators and students can receive feedback on conceptual understanding as and when required through the automated assessment of conceptual understanding, without the overhead of traditional formative assessment. Educators can implement accurate automated assessment of conceptual understanding models with fewer than 100 student responses for their short response questions.