Investigating the relationship of technology learning support to digital literacy from the perspective of self-determination theory

Chiu, Thomas K. F.; Sun, Jerry Chih‐Yuan; Ismailov, Murod

doi:10.1080/01443410.2022.2074966

Cited by 27 publications

(11 citation statements)

References 40 publications

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“…However, the lowest scores belonged to the second group. Studies have found a positive correlation between the use of digital resources and academic achievement [ 106 , 107 ] and the use of digital resources on student engagement and motivation, which can, in turn, lead to improved academic performance [ 108 ]. For example, the study by Chen & Jang [ 109 ] found that digital storytelling increased student motivation and engagement, improving academic performance.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of online learning readiness in the new distance learning normality

Reyes-Millán,

Villareal-Rodríguez,

Murrieta-Flores

et al. 2023

Heliyon

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Section: Discussionmentioning

confidence: 99%

Evaluation of online learning readiness in the new distance learning normality

Reyes-Millán,

Villareal-Rodríguez,

Murrieta-Flores

et al. 2023

Heliyon

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“…Third, this study presented insights and offered a parsimonious version of lower and higher cognitive domains for AI literacy development. Finally, AI literacy has to pay attention to both students' technological knowledge and skills, and moral mindsets so as to help students become responsible citizens (Chai et al., 2021, Chiu et al., 2022; Jobin et al., 2019; UNESCO, 2022). Considering prior research, AI literacy needs to reinforce students' socially appropriate behaviours (eg, reliability, safety, privacy, responsibility, accessibility, transparency and accountability) that are expected to reduce the negative consequences of the impact of technologies (Borenstein & Howard, 2021; Zhang et al., 2021).…”

Section: Discussionmentioning

confidence: 99%

Design and validation of the AI literacy questionnaire: The affective, behavioural, cognitive and ethical approach

Ng,

Wu,

Leung

et al. 2023

Brit J Educational Tech

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Artificial intelligence (AI) literacy is at the top of the agenda for education today in developing learners' AI knowledge, skills, attitudes and values in the 21st century. However, there are few validated research instruments for educators to examine how secondary students develop and perceive their learning outcomes. After reviewing the literature on AI literacy questionnaires, we categorized the identified competencies in four dimensions: (1) affective learning (intrinsic motivation and self‐efficacy/confidence), (2) behavioural learning (behavioural commitment and collaboration), (3) cognitive learning (know and understand; apply, evaluate and create) and (4) ethical learning. Then, a 32‐item self‐reported questionnaire on AI literacy (AILQ) was developed and validated to measure students' literacy development in the four dimensions. The design and validation of AILQ were examined through theoretical review, expert judgement, interview, pilot study and first‐ and second‐order confirmatory factor analysis. This article reports the findings of a pilot study using a preliminary version of the AILQ among 363 secondary school students in Hong Kong to analyse the psychometric properties of the instrument. Results indicated a four‐factor structure of the AILQ and revealed good reliability and validity. The AILQ is recommended as a reliable measurement scale for assessing how secondary students foster their AI literacy and inform better instructional design based on the proposed affective, behavioural, cognitive and ethical (ABCE) learning framework. Practitioner notesWhat is already known about this topic AI literacy has drawn increasing attention in recent years and has been identified as an important digital literacy. Schools and universities around the world started to incorporate AI into their curriculum to foster young learners' AI literacy. Some studies have worked to design suitable measurement tools, especially questionnaires, to examine students' learning outcomes in AI learning programmes. What this paper adds Develops an AI literacy questionnaire (AILQ) to evaluate students' literacy development in terms of affective, behavioural, cognitive and ethical (ABCE) dimensions. Proposes a parsimonious model based on the ABCE framework and addresses a skill set of AI literacy. Implications for practice and/or policy Researchers are able to use the AILQ as a guide to measure students' AI literacy. Practitioners are able to use the AILQ to assess students' AI literacy development.

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“…In support of implementing blended learning at universities, the UDL principles for course design are essential components of blended learning. Furthermore, to address the recent concern mentioned by academics and learners (Chiu, Sun & Ismailov, 2022) -a concern about the lack of student engagement (Strydom & Loots, 2022) during the 'emergency' response, where institutions of higher learning immediately had to transition from offline to online learning modalities -it is important to give full consideration to situational factors. Barkley (2010) defines student engagement as time and effort from the learners' side and resources and research-based teaching from the institution's side.…”

Section: Mnisimentioning

confidence: 99%

A case for deliberate and accommodative design for blended teaching and learning in universities in developing countries

Mnisi

2023

pie

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Since the emergence and development of digital technologies, the internet has quickly emerged as one of the most effective platforms for providing teachers and learners with access to resources for learning and sharing material. Universities in developing countries have limited access to digital technologies. At the few universitieswith access to digital technologies, there is arguably a lack of inclusive and accommodative pedagogy. Furthermore, challenges range from accessibility, administration, governance, and general lack of resources to inclusive module design due to inequalities. After the emergence of digital technologies, universities have had the benefit of curating some of their offerings to an ‘E-Learning’ mode, where learners and lecturers interact digitally. The technology part of the ‘blend’ is crucial, as it allows teachers and learners to interact beyond the classroom, form online communities of sharing ideas and debates, and learn according to their pace and environment. However, developing countries seem to be battling the challenge of transitioning from past teaching and learning policies, innovation, and education strategies. Furthermore, there have been several reasonable criticisms of the use of technology in education; some are concerned with the curriculum, knowledge, and pedagogy. Thus, this article caters for some criticisms using the theoretical framework research methodology. This article advocates blended learning and Universal Design for Learning (UDL) integration at universities in developing countries by relying on national and international studies. The UDL principles that this article advocates to be included in module and course design are multiple means of engagement, multiple means of representation, and multiple means of action and expression. Universities in developing countries experience unique challenges ranging from administrative, teaching and learning, and adaptation challenges due to a lack of resources and untrained academics and learners having to navigate the online learning environment.

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Investigating the relationship of technology learning support to digital literacy from the perspective of self-determination theory

Cited by 27 publications

References 40 publications

Evaluation of online learning readiness in the new distance learning normality

Evaluation of online learning readiness in the new distance learning normality

Design and validation of the AI literacy questionnaire: The affective, behavioural, cognitive and ethical approach

A case for deliberate and accommodative design for blended teaching and learning in universities in developing countries

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