Richard McInnes, James E Hobson, Kerry Lorette Johnson, Joshua Cramp, Claire Aitchison, K. Baldock
How do we make judgements about the quality of online courses? Checklists and rubrics are commonplace in Higher Education for establishing and measuring design features of online courses. They are created and used by institutions, academics, and educational designers to standardise measures for quality online course design. Despite an intensifying spotlight on quality learning and teaching in Higher Education, no large-scale review of course quality instruments has occurred. This scoping review aimed to ascertain the conceptions of quality being promoted by course quality evaluation instruments and the capability-building resources that underpin these instruments. Seventy-five instruments used to measure quality in online course design in Higher Education were identified via a systematic search. These instruments were charted and coded. This paper reports on findings that summarise the key attributes of the course quality evaluation instruments, conceptualises a shared definition of course quality, and proposes specific core criteria for measuring course quality under the domains of learning design, assessment and evaluation, usability and accessibility, social interaction, and technology. This scoping review found a concerning underrepresentation of capability-building resources associated with course quality instruments and recommends the capability-building potential of these tools shifting them from compliance checkers to enable skills development.
{"title":"Online Course Quality Evaluation Instruments: A Scoping Review","authors":"Richard McInnes, James E Hobson, Kerry Lorette Johnson, Joshua Cramp, Claire Aitchison, K. Baldock","doi":"10.14742/ajet.8978","DOIUrl":"https://doi.org/10.14742/ajet.8978","url":null,"abstract":"How do we make judgements about the quality of online courses? Checklists and rubrics are commonplace in Higher Education for establishing and measuring design features of online courses. They are created and used by institutions, academics, and educational designers to standardise measures for quality online course design. Despite an intensifying spotlight on quality learning and teaching in Higher Education, no large-scale review of course quality instruments has occurred. This scoping review aimed to ascertain the conceptions of quality being promoted by course quality evaluation instruments and the capability-building resources that underpin these instruments. \u0000 \u0000Seventy-five instruments used to measure quality in online course design in Higher Education were identified via a systematic search. These instruments were charted and coded. This paper reports on findings that summarise the key attributes of the course quality evaluation instruments, conceptualises a shared definition of course quality, and proposes specific core criteria for measuring course quality under the domains of learning design, assessment and evaluation, usability and accessibility, social interaction, and technology. This scoping review found a concerning underrepresentation of capability-building resources associated with course quality instruments and recommends the capability-building potential of these tools shifting them from compliance checkers to enable skills development.","PeriodicalId":502572,"journal":{"name":"Australasian Journal of Educational Technology","volume":"37 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140728049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiaochen Lin, Jeong Jin Yu, Qian Wang, Maria Limniou, Henk Huijser, Haibo Gu
People have different attitudes toward taking professional training courses online despite the post-pandemic movement towards e-learning in adult education. Limited studies have linked adult learners’ emotions with their attitudes towards technology (i.e., technology acceptance) and investigated their impacts on adult learners’ engagement in online professional development. This study aims to fulfil this gap by testing the mediating effect of technology acceptance between learning-related emotions and online learning engagement in professional development, and the moderating effect of emotion regulations therein. The study draws on the theoretical grounding from Control-Value Theory, Unified Theory of Acceptance and Use of Technology (UTAUT), and the Process Model of Emotion Regulation. After collecting data from 254 higher education faculty through an online questionnaire, the study applied a partial least squares structural equation model (PLS-SEM) for its results. The findings show that learning-related emotions are associated with technology acceptance and emotion regulation moderates those associations. Furthermore, the results suggest that technology acceptance mediates between learning-related emotions and online learning engagement. These findings strengthen the need to attend to affect in adults’ online learning and stress the importance of emotion in embracing technology for enhancing learning engagement among adult learners.
{"title":"role of learning-related emotions, emotion regulation and technology acceptance in learner engagement with online professional development","authors":"Xiaochen Lin, Jeong Jin Yu, Qian Wang, Maria Limniou, Henk Huijser, Haibo Gu","doi":"10.14742/ajet.9060","DOIUrl":"https://doi.org/10.14742/ajet.9060","url":null,"abstract":"People have different attitudes toward taking professional training courses online despite the post-pandemic movement towards e-learning in adult education. Limited studies have linked adult learners’ emotions with their attitudes towards technology (i.e., technology acceptance) and investigated their impacts on adult learners’ engagement in online professional development. This study aims to fulfil this gap by testing the mediating effect of technology acceptance between learning-related emotions and online learning engagement in professional development, and the moderating effect of emotion regulations therein. The study draws on the theoretical grounding from Control-Value Theory, Unified Theory of Acceptance and Use of Technology (UTAUT), and the Process Model of Emotion Regulation. After collecting data from 254 higher education faculty through an online questionnaire, the study applied a partial least squares structural equation model (PLS-SEM) for its results. The findings show that learning-related emotions are associated with technology acceptance and emotion regulation moderates those associations. Furthermore, the results suggest that technology acceptance mediates between learning-related emotions and online learning engagement. These findings strengthen the need to attend to affect in adults’ online learning and stress the importance of emotion in embracing technology for enhancing learning engagement among adult learners.","PeriodicalId":502572,"journal":{"name":"Australasian Journal of Educational Technology","volume":"23 15","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140732656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The impact of digital technologies on the ways people work, learn and live has been debated and researched for half a century. Digital literacy approaches have recurrently been the focus of educational and industry learning; however, current framings of digital literacy are not sufficient to support students’ digital capability development, nor do static digital literacies reflect the dynamic and contextual nature of digital capabilities. A digital capability continuum that fluidly moves between digital foundation skills, digital literacies and digital fluency is a more robust model for education. By unpacking the digital capability continuum and responding to both learning and curriculum paradigms, this paper expands on an earlier framework (Coldwell-Neilson, 2020), the decoding digital literacy framework, as well as building on our research and academic experiences, to inform higher education. A key agenda is that the higher education sector frames digital fluency as a mindset and an attitude. The model and framework underscore that capabilities need to be flexible and transferable across technologies, disciplines and the world of work.
{"title":"Digital fluency – a dynamic capability continuum","authors":"Kat Cain, Jo Coldwell-Neilson","doi":"10.14742/ajet.8363","DOIUrl":"https://doi.org/10.14742/ajet.8363","url":null,"abstract":"The impact of digital technologies on the ways people work, learn and live has been debated and researched for half a century. Digital literacy approaches have recurrently been the focus of educational and industry learning; however, current framings of digital literacy are not sufficient to support students’ digital capability development, nor do static digital literacies reflect the dynamic and contextual nature of digital capabilities. A digital capability continuum that fluidly moves between digital foundation skills, digital literacies and digital fluency is a more robust model for education. By unpacking the digital capability continuum and responding to both learning and curriculum paradigms, this paper expands on an earlier framework (Coldwell-Neilson, 2020), the decoding digital literacy framework, as well as building on our research and academic experiences, to inform higher education. A key agenda is that the higher education sector frames digital fluency as a mindset and an attitude. The model and framework underscore that capabilities need to be flexible and transferable across technologies, disciplines and the world of work.","PeriodicalId":502572,"journal":{"name":"Australasian Journal of Educational Technology","volume":"17 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139865811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The impact of digital technologies on the ways people work, learn and live has been debated and researched for half a century. Digital literacy approaches have recurrently been the focus of educational and industry learning; however, current framings of digital literacy are not sufficient to support students’ digital capability development, nor do static digital literacies reflect the dynamic and contextual nature of digital capabilities. A digital capability continuum that fluidly moves between digital foundation skills, digital literacies and digital fluency is a more robust model for education. By unpacking the digital capability continuum and responding to both learning and curriculum paradigms, this paper expands on an earlier framework (Coldwell-Neilson, 2020), the decoding digital literacy framework, as well as building on our research and academic experiences, to inform higher education. A key agenda is that the higher education sector frames digital fluency as a mindset and an attitude. The model and framework underscore that capabilities need to be flexible and transferable across technologies, disciplines and the world of work.
{"title":"Digital fluency – a dynamic capability continuum","authors":"Kat Cain, Jo Coldwell-Neilson","doi":"10.14742/ajet.8363","DOIUrl":"https://doi.org/10.14742/ajet.8363","url":null,"abstract":"The impact of digital technologies on the ways people work, learn and live has been debated and researched for half a century. Digital literacy approaches have recurrently been the focus of educational and industry learning; however, current framings of digital literacy are not sufficient to support students’ digital capability development, nor do static digital literacies reflect the dynamic and contextual nature of digital capabilities. A digital capability continuum that fluidly moves between digital foundation skills, digital literacies and digital fluency is a more robust model for education. By unpacking the digital capability continuum and responding to both learning and curriculum paradigms, this paper expands on an earlier framework (Coldwell-Neilson, 2020), the decoding digital literacy framework, as well as building on our research and academic experiences, to inform higher education. A key agenda is that the higher education sector frames digital fluency as a mindset and an attitude. The model and framework underscore that capabilities need to be flexible and transferable across technologies, disciplines and the world of work.","PeriodicalId":502572,"journal":{"name":"Australasian Journal of Educational Technology","volume":"45 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139806084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Recent advances and applications of artificial intelligence (AI) have increased the opportunities for students to interact with AI in their learning tasks. Although various fields of scholarly research have investigated human-AI collaboration, the underlying processes of how students collaborate with AI in a student-AI teaming scenario have been scarcely investigated. To develop effective AI applications in education, it is necessary to understand differences in the student-AI interaction (SAI) process depending on students' characteristics. The present study attempts to fill this gap by exploring the differences in the SAI process amongst students with varying drawing proficiencies and attitudes towards AI in performing a public advertisement drawing task. Based on the empirical evidence obtained from the think-aloud protocols of 20 Korean undergraduate students, the study first conducted a lag sequential analysis to identify statistically significant linear patterns of each group and then chronologically incorporated them into the SAI duration via coded activity alignment series to distinguish the overall SAI process of each group. The study revealed the distinctive differences in SAI processes of students with different attitudes towards AI and drawing skills. To better facilitate student-AI teams for learning, a range of implications of educational AI development and instructional design is discussed. Implications for practice or policy: Educational AI should not be limited to performing a specific task and solving well-defined problems. It should be designed with a holistic view of the end-to-end student-AI process, interconnected to different learning activities in the learning process. Educational AI should be capable of increasing students’ metacognition and emotional engagement. An educational AI system architect team inclusive of diverse stakeholders should be formed to collaboratively design the AI system.
人工智能（AI）的最新进展和应用增加了学生在学习任务中与人工智能互动的机会。虽然学术研究的各个领域都对人与人工智能的协作进行了调查，但对学生与人工智能组队场景中学生如何与人工智能协作的基本过程却鲜有研究。为了在教育领域开发有效的人工智能应用，有必要了解学生与人工智能互动（SAI）过程中因学生特点而产生的差异。本研究试图填补这一空白，探索不同绘画水平和对人工智能态度的学生在完成公共广告绘画任务时的 SAI 过程差异。基于从 20 名韩国本科生的思考-朗读协议中获得的经验证据，本研究首先进行了滞后序列分析，以确定各组在统计上具有显著意义的线性模式，然后通过编码活动排列序列将其按时间顺序纳入 SAI 持续时间，以区分各组的整体 SAI 过程。该研究揭示了对人工智能和绘画技能持不同态度的学生在 SAI 过程中的明显差异。为了更好地促进学生-人工智能团队的学习，探讨了人工智能教育发展和教学设计的一系列意义。对实践或政策的启示：教育人工智能不应局限于执行特定任务和解决定义明确的问题。教育人工智能应能提高学生的元认知和情感参与度。应组建一个由不同利益相关者组成的教育人工智能系统架构师团队，共同设计人工智能系统。
{"title":"Differences in student-AI interaction process on a drawing task: Focusing on students’ attitude towards AI and the level of drawing skills","authors":"Jinhee Kim, Yoonhee Ham, Sang-Soog Lee","doi":"10.14742/ajet.8859","DOIUrl":"https://doi.org/10.14742/ajet.8859","url":null,"abstract":"Recent advances and applications of artificial intelligence (AI) have increased the opportunities for students to interact with AI in their learning tasks. Although various fields of scholarly research have investigated human-AI collaboration, the underlying processes of how students collaborate with AI in a student-AI teaming scenario have been scarcely investigated. To develop effective AI applications in education, it is necessary to understand differences in the student-AI interaction (SAI) process depending on students' characteristics. The present study attempts to fill this gap by exploring the differences in the SAI process amongst students with varying drawing proficiencies and attitudes towards AI in performing a public advertisement drawing task. Based on the empirical evidence obtained from the think-aloud protocols of 20 Korean undergraduate students, the study first conducted a lag sequential analysis to identify statistically significant linear patterns of each group and then chronologically incorporated them into the SAI duration via coded activity alignment series to distinguish the overall SAI process of each group. The study revealed the distinctive differences in SAI processes of students with different attitudes towards AI and drawing skills. To better facilitate student-AI teams for learning, a range of implications of educational AI development and instructional design is discussed.\u0000 \u0000Implications for practice or policy:\u0000\u0000Educational AI should not be limited to performing a specific task and solving well-defined problems. It should be designed with a holistic view of the end-to-end student-AI process, interconnected to different learning activities in the learning process.\u0000Educational AI should be capable of increasing students’ metacognition and emotional engagement.\u0000An educational AI system architect team inclusive of diverse stakeholders should be formed to collaboratively design the AI system.\u0000","PeriodicalId":502572,"journal":{"name":"Australasian Journal of Educational Technology","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139885258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Recent advances and applications of artificial intelligence (AI) have increased the opportunities for students to interact with AI in their learning tasks. Although various fields of scholarly research have investigated human-AI collaboration, the underlying processes of how students collaborate with AI in a student-AI teaming scenario have been scarcely investigated. To develop effective AI applications in education, it is necessary to understand differences in the student-AI interaction (SAI) process depending on students' characteristics. The present study attempts to fill this gap by exploring the differences in the SAI process amongst students with varying drawing proficiencies and attitudes towards AI in performing a public advertisement drawing task. Based on the empirical evidence obtained from the think-aloud protocols of 20 Korean undergraduate students, the study first conducted a lag sequential analysis to identify statistically significant linear patterns of each group and then chronologically incorporated them into the SAI duration via coded activity alignment series to distinguish the overall SAI process of each group. The study revealed the distinctive differences in SAI processes of students with different attitudes towards AI and drawing skills. To better facilitate student-AI teams for learning, a range of implications of educational AI development and instructional design is discussed. Implications for practice or policy: Educational AI should not be limited to performing a specific task and solving well-defined problems. It should be designed with a holistic view of the end-to-end student-AI process, interconnected to different learning activities in the learning process. Educational AI should be capable of increasing students’ metacognition and emotional engagement. An educational AI system architect team inclusive of diverse stakeholders should be formed to collaboratively design the AI system.
人工智能（AI）的最新进展和应用增加了学生在学习任务中与人工智能互动的机会。虽然学术研究的各个领域都对人与人工智能的协作进行了调查，但对学生与人工智能组队场景中学生如何与人工智能协作的基本过程却鲜有研究。为了在教育领域开发有效的人工智能应用，有必要了解学生与人工智能互动（SAI）过程中因学生特点而产生的差异。本研究试图填补这一空白，探索不同绘画水平和对人工智能态度的学生在完成公共广告绘画任务时的 SAI 过程差异。基于从 20 名韩国本科生的思考-朗读协议中获得的经验证据，本研究首先进行了滞后序列分析，以确定各组在统计上具有显著意义的线性模式，然后通过编码活动排列序列将其按时间顺序纳入 SAI 持续时间，以区分各组的整体 SAI 过程。该研究揭示了对人工智能和绘画技能持不同态度的学生在 SAI 过程中的明显差异。为了更好地促进学生-人工智能团队的学习，探讨了人工智能教育发展和教学设计的一系列意义。对实践或政策的启示：教育人工智能不应局限于执行特定任务和解决定义明确的问题。教育人工智能应能提高学生的元认知和情感参与度。应组建一个由不同利益相关者组成的教育人工智能系统架构师团队，共同设计人工智能系统。
{"title":"Differences in student-AI interaction process on a drawing task: Focusing on students’ attitude towards AI and the level of drawing skills","authors":"Jinhee Kim, Yoonhee Ham, Sang-Soog Lee","doi":"10.14742/ajet.8859","DOIUrl":"https://doi.org/10.14742/ajet.8859","url":null,"abstract":"Recent advances and applications of artificial intelligence (AI) have increased the opportunities for students to interact with AI in their learning tasks. Although various fields of scholarly research have investigated human-AI collaboration, the underlying processes of how students collaborate with AI in a student-AI teaming scenario have been scarcely investigated. To develop effective AI applications in education, it is necessary to understand differences in the student-AI interaction (SAI) process depending on students' characteristics. The present study attempts to fill this gap by exploring the differences in the SAI process amongst students with varying drawing proficiencies and attitudes towards AI in performing a public advertisement drawing task. Based on the empirical evidence obtained from the think-aloud protocols of 20 Korean undergraduate students, the study first conducted a lag sequential analysis to identify statistically significant linear patterns of each group and then chronologically incorporated them into the SAI duration via coded activity alignment series to distinguish the overall SAI process of each group. The study revealed the distinctive differences in SAI processes of students with different attitudes towards AI and drawing skills. To better facilitate student-AI teams for learning, a range of implications of educational AI development and instructional design is discussed.\u0000 \u0000Implications for practice or policy:\u0000\u0000Educational AI should not be limited to performing a specific task and solving well-defined problems. It should be designed with a holistic view of the end-to-end student-AI process, interconnected to different learning activities in the learning process.\u0000Educational AI should be capable of increasing students’ metacognition and emotional engagement.\u0000An educational AI system architect team inclusive of diverse stakeholders should be formed to collaboratively design the AI system.\u0000","PeriodicalId":502572,"journal":{"name":"Australasian Journal of Educational Technology","volume":"93 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139825306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper explores international students’ engagement with educational technology for self-regulated English learning at an Australian university. Despite the increased use of automated feedback systems (AFSs) for language assessment, students’ critical engagement with them for independent learning remains under-researched. The study primarily employed a qualitative approach to understand the students’ preferred AFS tools and critical engagement throughout their personalised learning journeys but it also included a small-scale quantitative component. Data were gathered from seven students’ e-portfolios, focus group interviews as well as a survey among 32 participants. Results highlight positive perceptions and successful use of AFSs, with students leveraging these tools to identify improvement areas, track progress and gain confidence. The study emphasises the importance of course structure, teacher guidance and a combination of human and automated feedback, in fostering learner autonomy and emotional self-regulation. The paper underscores the potential for sustained use of AFSs beyond the cours, and the significance of guiding learners to critically use these tools for ongoing learning and growth rather than dependence. These findings have significant implications, as readily available artificial intelligence tools such as ChatGPT hold great pedagogical potential for self-regulated learning within and beyond the language learning field. Implications for practice or policy Instructors can use AFSs as effective tools to help English learners in higher education when scaffolding critical engagement with automated feedback and emotional self-regulation and providing adaptability, as such scaffolding and flexibility are essential for mitigating the limitations of AFSs. Course leaders and universities should consider investing in AFSs as they can elevate the availability and sustainability of feedback for language enhancement and potentially any other type of learning.
{"title":"It is like a friend to me: Critical usage of automated feedback systems by self-regulating English learners in higher education","authors":"Long Li, Mira Kim","doi":"10.14742/ajet.8821","DOIUrl":"https://doi.org/10.14742/ajet.8821","url":null,"abstract":"This paper explores international students’ engagement with educational technology for self-regulated English learning at an Australian university. Despite the increased use of automated feedback systems (AFSs) for language assessment, students’ critical engagement with them for independent learning remains under-researched. The study primarily employed a qualitative approach to understand the students’ preferred AFS tools and critical engagement throughout their personalised learning journeys but it also included a small-scale quantitative component. Data were gathered from seven students’ e-portfolios, focus group interviews as well as a survey among 32 participants. Results highlight positive perceptions and successful use of AFSs, with students leveraging these tools to identify improvement areas, track progress and gain confidence. The study emphasises the importance of course structure, teacher guidance and a combination of human and automated feedback, in fostering learner autonomy and emotional self-regulation. The paper underscores the potential for sustained use of AFSs beyond the cours, and the significance of guiding learners to critically use these tools for ongoing learning and growth rather than dependence. These findings have significant implications, as readily available artificial intelligence tools such as ChatGPT hold great pedagogical potential for self-regulated learning within and beyond the language learning field.\u0000 \u0000Implications for practice or policy\u0000\u0000Instructors can use AFSs as effective tools to help English learners in higher education when scaffolding critical engagement with automated feedback and emotional self-regulation and providing adaptability, as such scaffolding and flexibility are essential for mitigating the limitations of AFSs.\u0000Course leaders and universities should consider investing in AFSs as they can elevate the availability and sustainability of feedback for language enhancement and potentially any other type of learning.\u0000","PeriodicalId":502572,"journal":{"name":"Australasian Journal of Educational Technology","volume":"117 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139614048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this editorial we reflect on the last three years of AJET achievements, challenges, and opportunities as we reach a time of transition in the lead editorial team. We also reflect on the key themes of 2023, especially the impact that the growing availability of generative artificial intelligence has had on research and practice in the tertiary education sector. We present our annual round up of bibliometrics, thank our hardworking editorial team, and acknowledge the contributions of those who are ending their service with AJET in 2023. In conclusion, we look ahead by outlining our goals for 2024 and discussing the themes and technologies that will be a focus for AJET in the new year.
{"title":"AJET in 2023: Reflections on educational technology, people, and bibliometrics","authors":"L. Corrin, Kate Thompson, J. Lodge","doi":"10.14742/ajet.9277","DOIUrl":"https://doi.org/10.14742/ajet.9277","url":null,"abstract":"In this editorial we reflect on the last three years of AJET achievements, challenges, and opportunities as we reach a time of transition in the lead editorial team. We also reflect on the key themes of 2023, especially the impact that the growing availability of generative artificial intelligence has had on research and practice in the tertiary education sector. We present our annual round up of bibliometrics, thank our hardworking editorial team, and acknowledge the contributions of those who are ending their service with AJET in 2023. In conclusion, we look ahead by outlining our goals for 2024 and discussing the themes and technologies that will be a focus for AJET in the new year.","PeriodicalId":502572,"journal":{"name":"Australasian Journal of Educational Technology","volume":" 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139136189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Md. Shahinur Rahman, M. Sabbir, Dr. Jing Zhang, Iqbal Hossain Moral, Gazi Md. Shakhawat Hossain
Little knowledge is available on students’ attitudes and behavioural intentions towards using ChatGPT, a breakthrough innovation in recent times. This study bridges this gap by adding two relevant less-explored constructs (i.e., perceived enjoyment and perceived informativeness) to the technology acceptance model and illustrating the moderating effect of trust on the acceptance of ChatGPT. Data was collected from 344 private and public university students from Bangladesh, with the analysis done through structural equation modelling. The results highlight the significance of perceived usefulness, perceived ease of use and perceived informativeness in understanding students’ attitudes towards using ChatGPT for learning, which subsequently predicts their behavioural intention to use it. Interestingly, students’ level of enjoyment was triggered once the trust issue came into play, meaning perceived enjoyment had no substantial impact on attitude unless trust moderates the relationship between perceived enjoyment and attitude towards using ChatGPT. Implications for practice or policy Scholars can get first-hand insights into perceived enjoyment and perceived informativeness with perceived usefulness and perceived ease of use in the context of ChatGPT and education. Practitioners and educators can comprehensively understand the antecedents affecting students’ attitudes in line with their behavioural intention towards ChatGPT. Policymakers can design viable strategies to promote the ethical and sustainable usage of ChatGPT in education.
{"title":"Examining students’ intention to use ChatGPT: Does trust matter?","authors":"Md. Shahinur Rahman, M. Sabbir, Dr. Jing Zhang, Iqbal Hossain Moral, Gazi Md. Shakhawat Hossain","doi":"10.14742/ajet.8956","DOIUrl":"https://doi.org/10.14742/ajet.8956","url":null,"abstract":"Little knowledge is available on students’ attitudes and behavioural intentions towards using ChatGPT, a breakthrough innovation in recent times. This study bridges this gap by adding two relevant less-explored constructs (i.e., perceived enjoyment and perceived informativeness) to the technology acceptance model and illustrating the moderating effect of trust on the acceptance of ChatGPT. Data was collected from 344 private and public university students from Bangladesh, with the analysis done through structural equation modelling. The results highlight the significance of perceived usefulness, perceived ease of use and perceived informativeness in understanding students’ attitudes towards using ChatGPT for learning, which subsequently predicts their behavioural intention to use it. Interestingly, students’ level of enjoyment was triggered once the trust issue came into play, meaning perceived enjoyment had no substantial impact on attitude unless trust moderates the relationship between perceived enjoyment and attitude towards using ChatGPT. Implications for practice or policy Scholars can get first-hand insights into perceived enjoyment and perceived informativeness with perceived usefulness and perceived ease of use in the context of ChatGPT and education. Practitioners and educators can comprehensively understand the antecedents affecting students’ attitudes in line with their behavioural intention towards ChatGPT. Policymakers can design viable strategies to promote the ethical and sustainable usage of ChatGPT in education.","PeriodicalId":502572,"journal":{"name":"Australasian Journal of Educational Technology","volume":"53 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139172746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Christopher Bridge, D. Horey, Birgit Loch, Brianna Julien, Belinda Thompson
Realising the full potential for educational technologies to improve the student experience is a challenge for higher education institutions. Although academic resistance is often blamed for poor dissemination of teaching technologies, recent literature has more satisfactorily framed the issue in terms of intransigent organisational culture. Features of higher education organisational culture that are conducive to innovation include senior executive support, freedom to experiment and permission to fail and interdisciplinary and cross-institutional engagement. One approach to changing organisational culture is to establish new organisational structures embodying positive traits. This study qualitatively evaluated a technology in teaching innovators group established in 2018 in a science, health and engineering faculty of an Australian university; it provides evidence that the group improved the culture of teaching technology innovation by creating a safe space for innovation, which members then disseminated into their departmental communities. The study also found that the group created a forum for teaching technology innovators to engage with stakeholders in the university’s learning and teaching and information and communication technology units, leading to improved outcomes for the university’s learning environment. Implications for practice or policy Teaching technology dissemination in higher education can be enhanced through a community of practice model. Higher education learning technology environments can be improved through an innovators group leading to greater cross-institutional collaboration. Educational technology staff may be able to overcome academic resistance to strategic projects by pursuing a community of practice approach.
{"title":"The impact of an innovators group on the development of a culture of innovation in the use of educational technologies","authors":"Christopher Bridge, D. Horey, Birgit Loch, Brianna Julien, Belinda Thompson","doi":"10.14742/ajet.8575","DOIUrl":"https://doi.org/10.14742/ajet.8575","url":null,"abstract":"Realising the full potential for educational technologies to improve the student experience is a challenge for higher education institutions. Although academic resistance is often blamed for poor dissemination of teaching technologies, recent literature has more satisfactorily framed the issue in terms of intransigent organisational culture. Features of higher education organisational culture that are conducive to innovation include senior executive support, freedom to experiment and permission to fail and interdisciplinary and cross-institutional engagement. One approach to changing organisational culture is to establish new organisational structures embodying positive traits. This study qualitatively evaluated a technology in teaching innovators group established in 2018 in a science, health and engineering faculty of an Australian university; it provides evidence that the group improved the culture of teaching technology innovation by creating a safe space for innovation, which members then disseminated into their departmental communities. The study also found that the group created a forum for teaching technology innovators to engage with stakeholders in the university’s learning and teaching and information and communication technology units, leading to improved outcomes for the university’s learning environment. Implications for practice or policy Teaching technology dissemination in higher education can be enhanced through a community of practice model. Higher education learning technology environments can be improved through an innovators group leading to greater cross-institutional collaboration. Educational technology staff may be able to overcome academic resistance to strategic projects by pursuing a community of practice approach.","PeriodicalId":502572,"journal":{"name":"Australasian Journal of Educational Technology","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139235181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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