Learning analytics support to teachers' design and orchestrating tasks

Amarasinghe, Ishari; Michos, Konstantinos; Crespi, Francisco; Hernández‐Leo, Davinia

doi:10.1111/jcal.12711

Cited by 5 publications

(3 citation statements)

References 45 publications

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“…Therefore, future research should also focus on systems that include sufficient intelligent guidance that would not only require less training but that will also be perceived as useful by teachers. To accomplish this aim, teachers (together with learners) should be an essential part of the development process from an early stage, such as through the implementation of a participatory design approach, as suggested by recent initiatives on human-centred LA [24,49,50]. Only a few of the papers under review took a similar approach, as also shown by the lack of related topics in our analyses.…”

Section: Discussionmentioning

confidence: 99%

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Model-Based Learning Analytics for a Partnership of Teachers and Intelligent Systems: A Bibliometric Systematic Review

et al. 2023

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This paper presents a bibliometric systematic review on model-based learning analytics (MbLA), which enable coupling between teachers and intelligent systems to support the learning process. This is achieved through systems that make their models of student learning and instruction transparent to teachers. We use bibliometric network analysis and topic modelling to explore the synergies between the related research groups and the main research topics considered in the 42 reviewed papers. Network analysis depicts an early stage community, made up of several research groups, mainly from the fields of learning analytics and intelligent tutoring systems, which have had little explicit and implicit collaboration but do share a common core literature. Th resulting topics from the topic modelling can be grouped into the ones related to teacher practices, such as awareness and reflection, learning orchestration, or assessment frameworks, and the ones related to the technology used to open up the models to teachers, such as dashboards or adaptive learning architectures. Moreover, results show that research in MbLA has taken an individualistic approach to student learning and instruction, neglecting social aspects and elements of collaborative learning. To advance research in MbLA, future research should focus on hybrid teacher–AI approaches that foster the partnership between teachers and technology to support the learning process, involve teachers in the development cycle from an early stage, and follow an interdisciplinary approach.

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Section: Discussionmentioning

confidence: 99%

“…Collaborative models that model how collaborative learning should be conducted (e.g., through a collaborative learning script that is computational and open to teachers, such as in [24]). • Social models that include information about the social structure of a group of students (see, for instance, [25]).…”

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confidence: 99%

Model-Based Learning Analytics for a Partnership of Teachers and Intelligent Systems: A Bibliometric Systematic Review

et al. 2023

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“…Teachers can supervise and help learners gain knowledge correctly. Furthermore, a teacher can help to deliver knowledge content to learners with a suitable learning approach [15]. However, most teachers lack the time to teach the learners more deeply [16].…”

Section: The Shifting Perspective On Educationmentioning

confidence: 99%

X-Education: Education of All Things with AI and Edge Computing—One Case Study for EFL Learning

Hwang

Nurtantyana

2022

Sustainability

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Education usually only focuses on how to educate human beings with pedagogical or technical support. However, with artificial intelligence (AI) and edge computing, education can be extended and considered not only to educate human beings but also all things, such as physical or digital things. In this study, all things are given the opportunity to learn more about themselves and build their knowledge through interactions with other things, people, and AI agents. Thus, the X-Education framework is proposed in this study for educating all things, including human beings, physical, digital, and AI agents. One preliminary study for EFL writing was conducted to investigate not only whether all things can speed up their knowledge but also whether EFL learners as humans can also obtain the benefits of using X-Education. Further, the forwarding mechanisms of questioning and answering (Q&A) were designed to speed up interactions among all things. In total, 22 learners were divided into two groups, the experimental group (EG) and the control group (CG), with/without the Q&A forwarding mechanisms, respectively. A mixed-method approach with the two experimental phases was used in this study. The results showed that the knowledge of all things in the EG increased significantly more than the CG. Moreover, the EG received better EFL answers from the on-device AI with the forwarding mechanisms. They also felt that X-Education could help them to learn EFL writing better through Q&A. Furthermore, it was demonstrated that X-Education can accommodate not only humans but also all things to improve their knowledge.

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Technology-Enhanced Collaborative Inquiry in K–12 Classrooms: A Systematic Review of Empirical Studies

Chen,

Chen

2024

Sci & Educ

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Collaborative inquiry is an instructional approach that encourages student groups to engage in scientific inquiry processes, thereby enhancing their critical thinking and exploratory skills. The effective classroom implementation of this method requires ensuring student engagement in each inquiry stage, where technological tools and activity strategies play a crucial role in supporting their inquiry processes. However, the technological tools and activity strategies that contribute to designing classroom activities and fostering students’ engagement in collaborative inquiry remain unclear. This systematic review analyzed 58 empirical studies on technology-enhanced collaborative inquiry in K–12 classrooms. We examined the characteristics of these studies, the technological tools and activity strategies employed, and their reported outcomes and effects on student learning. The results indicate that most classroom practices featured diverse technological tools and activity strategies to support students in collaboratively performing stages of inquiry tasks. The findings highlight the need for further research into effectively integrating technological tools with activity strategies to provide adaptive support for specific inquiry processes, such as hypothesis generation and scientific argumentation. Our synthesis of previous outcome measurements revealed the positive impacts of technology-enhanced collaborative inquiry on students’ content knowledge, overall inquiry process, and scientific skills like argumentation. The implications of these findings are discussed for both researchers and practitioners, emphasizing the necessity of integrating appropriate technological tools and activity strategies to effectively facilitate collaborative inquiry in K–12 classrooms.

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Learning analytics support to teachers' design and orchestrating tasks

Cited by 5 publications

References 45 publications

Model-Based Learning Analytics for a Partnership of Teachers and Intelligent Systems: A Bibliometric Systematic Review

Model-Based Learning Analytics for a Partnership of Teachers and Intelligent Systems: A Bibliometric Systematic Review

X-Education: Education of All Things with AI and Edge Computing—One Case Study for EFL Learning

Technology-Enhanced Collaborative Inquiry in K–12 Classrooms: A Systematic Review of Empirical Studies

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