Koh, Elizabeth

In the past two decades, the field of Machine Learning has not only greatly expanded in terms of the plethora of increasingly powerful modeling frameworks it has provided, but has also birthed the applied fields of Educational Data Mining and Learning Analytics. Learning Analytics has blossomed as an area in the Learning Sciences, promising impact for various stakeholders working at different educational levels, such as Instructional Designers, Students, Instructors, Policymakers and Administrators. This symposium offers a taste of cutting edge work across each of these levels, with a common emphasis on analytics applied to social processes.

In the field of learning analytics (LA), actionable insight from LA designs tends to be a buzzword without clear understandings. As the teacher is a key stakeholder, what teacher-actionable insights can be derived from LA designs? Towards providing greater clarity on this issue, we concretize a taxonomy of LA decision support for teacher-actionable insights in student engagement. Four types of decision support are conceived in this taxonomy with relevant teacher implications. Through this taxonomy, we hope to offer possible pathways for actionable insight in LA designs and make clearer the role of the teacher.

In the emerging field of learning analytics (LA), actionable insight from LA designs tends to be a buzzword without clear understandings. Student engagement is commonly measured in LA designs and used to inform actionable insight. Moreover, in K-12 education, where the teacher is a key stakeholder, what teacher-actionable insights can be derived from LA designs? Towards providing greater clarity on this issue, we concretize a taxonomy of LA decision support for teacher-actionable insights in student engagement. Four types of decision support are conceived in this taxonomy with relevant teacher implications. Through this taxonomy, we hope to offer possible pathways for actionable insight in LA designs and make clearer the role of the teacher.

Teamwork is an important twenty-first-century competency to be nurtured in our young. In this eduLab Information and Communications Technology (ICT) innovation, My Groupwork Buddy (MGB), a techno-pedagogical system, was developed using design-based research for secondary school students in collaborative inquiry projects from any subject domain. Co-designed with a team of researchers, teachers and education officers, MGB aimed to nurture teamwork competency through its blended pedagogical framework, formative assessment measures and a web-based learning analytics system. The innovation was successfully trialled over two and a half years in two schools, across two subjects, and used by 12 teachers and over 200 students. This chapter will examine the enablers and impediments of infusing the innovation from the design team’s perspective. Insights of key conditions for the innovation to take root, and its possible infusion in the school system will be discussed. Practical implications for practice and policy will also be described in light of MGB’s journey in Singapore’s educational context.

The affordances of learning analytics (LA) tools and solutions are being increasingly harnessed for enhancing 21st century pedagogical and learning strategies and outcomes. However, use cases and empirical understandings of students’ experiences with LA tools and environments aimed at fostering 21st century literacies, especially in the K-12 schooling sector and in Asian education contexts remain relatively scarce in the field. Our paper addresses this knowledge gap in two ways. First, we present a first iteration design of a computer-supported collaborative critical reading and LA environment, WiREAD, and its 16-week implementation in a Singapore high school. Second, we foreground students’ evaluative accounts of the benefits and drawbacks associated with this techno-pedagogical innovation. Our analysis of students’ collective sense-making pointed to a number of potentialities and perils associated with the design and use of LA dashboards. Positives included (1) fostering greater self-awareness, reflective and self-regulatory learning dispositions, (2) enhancing learning motivation and engagement, and (3) nurturing connective literacy among students. The motivational value of peer-referenced LA visualisations for stimulating healthy competition and game-like learning was identified, alongside the perils of these serving to demoralise, pressurise and trigger complacency in learners. By focusing on students’ experiences and interpretations of how the LA dashboard visualizations impacted their learning motivation and outcomes, this paper aims to shed insights into the pedagogical complexities of designing LA that considers the voices of learners as a critical stakeholder group.

Artificial Intelligence (AI) in education and learning analytics (LA) tools are increasingly being developed and implemented to enhance teaching and learning within Singapore’s education landscape. This paper provides an overview of key AI in education and LA projects and initiatives in Singapore, organized by the types of technology. The identified projects and initiatives involve a range of techniques and systems to achieve personalized learning, improve student engagement, optimize resources, and also predict student success among a list of educational outcomes. We briefly describe each identified project before further discussing the collective impact and limitations, as well as the implications for Singapore and her education environments. Overall, this paper seeks to provide an overview of the state and use of AI and LA in education-related projects within Singapore and highlights the need for further research and development in this area to fully realize the potential of these technologies for improvement of teaching and learning.

Teamwork is an important competency for 21st century learner. However, equipping students with an awareness of their teamwork behaviors is difficult. This paper therefore aims to develop a model that will analyze student dialogue to identify teamwork indicators that will serve as formative feedback for students. Four dimensions of teamwork namely coordination, mutual performance monitoring, constructive conflict and team emotional support are measured. In addition, the paper explores multi-label classification approaches combined with feature engineering techniques to classify student chat data. The results show that by incorporating linguistic features, it is possible to achieve better performance in identifying the teamwork indicators in student dialogue.

Networked learning provides opportunities for learners to develop their critical thinking, an important 21st century competency, through dialogue with fellow learners to consider other perspectives and negotiate and critique ideas and arguments. However, much extant literature has not examined networked learning environments among younger learners nor the optimal conditions for enhancing critical thinking. Therefore, a study was carried out to investigate these conditions. A learning analytics networked learning environment was designed and 264 secondary three students participated in the 10-week long intervention as part of their English curriculum. Individual and collective social network metrics, critical reading scores, and self-reported survey data were used to quantitatively evaluate students’ critical reading performance in relation to their participation in networked learning. Results highlight several optimal conditions, notably that it is not just participation of the learner that enhances critical thinking but the learners’ reciprocity in replying and the distance of those posts in the network. Discussions and implications of the findings follow to provide insightful understanding of how the rich and complex settings of networked learning can enhance critical thinking capacities in secondary schooling.

This paper foregrounds teacher practitioners’ implementation experiences and reflections of a web-based Collaborative Video Annotation and Learning Analytics (CoVAA) intervention aimed at enhancing video-based teaching and learning in schools, with a view to foster secondary students’ conceptual understanding, social knowledge construction, and self-regulated learning dispositions. We first briefly outline the key learning principles that underpin the design of CoVAA, namely social dialogic learning, assessment for learning, and computer-supported collaborative learning. Next, we explain its two key learning affordances: (i) timepoint-based collaborative video annotation supplemented by a live interactive chatboard, and (ii) rapid digital formative feedback in the form of teacher and learner dashboards. We then illustrate how teachers implement these in their classrooms. Teachers’ sense-making of the learning and teaching gains, challenges and pathways forward for leveraging on these contemporary digital social learning affordances to enhance video-based classroom practices are presented and discussed.