Transforming Teaching and Learning Through Emerging Technologies–Integrated Learning Analytics

• In Event: Making Constructivist Learning Feasible: Exploring Convergence of Virtual Reality and Learning Analytics for Future Research Directions

Abstract

Opportunities to learn are critical to reach excellence in education. These opportunities should occur throughout an individual’s lifespan because learning challenging ideas is not developmentally inevitable; moreover, it takes time and is dependent on experiences and education (National Research Council [NRC], 2007). In response to the vision of opportunities to learn, a learning progression (LP) is proposed as a framework to develop curriculum, professional learning, instruction, and assessment coherently for supporting students' meaningful experiences on a topic over a broad span of time (Shin et al, 2019). Researchers in LP focus their work on the creation of fruitful learning environments with the goal of increasing students’ meaningful experiences to make sense of challenging situations or complex problems, helping them develop deeper understanding, and monitoring learning growth over time (NRC, 2012). Emerging technologies such as augmented Reality (AR) – a real-time technology blending of real-world and computer-generated information – have potential to enhance learning by involving students in authentic environments with meaningful experiences (Horizon Report, 2011; Fernández-Batanero, et al., 2022).

However, while emerging technologies provide potentially transformative added value in education, it simultaneously for teachers face complex challenges in implementing innovative curricula. The unique challenges are conducting ongoing formative assessment over time and providing timely feedback to students’ needs, particularly when teaching in large and diverse classrooms. Emerging technology isn’t enough to get students involved in deep understanding. To support students meaningfully, teachers need to interpret students’ performance on activities, recognize patterns of performance in the classroom, and respond with appropriate interventions.

What the emerging technologies in education to date are missing is a built-in system of feedback on students’ performances while students engage in learning activities. The emerging technologies are based on real locations, real data, and real practices; but they do not incorporate a dynamic system to provide real-time feedback for teaching and learning. To build more robust system that reflects the vision for constructive learning, it is necessary to expand current research with richer data sources including text-based writing and speech, dialogues among students, body motions, logfile data generated from interactive AR, student engagement metrics, data from formative and summative assessments– as well as monitoring student progress longitudinally as their understanding develops. A new approach such as learning analytics needs to analyze and synthesize diverse data on each student, follow longitudinal learning-growth of students, find the known student progression and learning patterns, further discover new patterns, and extend the studies toward building new methodologies for education.

The research on emerging technology is still in its initial stage, in particular monitoring students’ performances using heterogeneous data types longitudinally. Synergistic integration of emerging technologies with learning analytics has potential addressing challenges of core issues in education (e.g., students’ engagement, mastery of sophisticated knowledge and skills, transfer of learning, and attaining scale). The overarching objectives should be dedicated to building teaching and learning tools and resources to support teachers in creating and sustaining rich, student-focused learning environments to meaningfully assess over time, provide timely feedback, and respond to student and class needs.

Author

• Namsoo Shin, Michigan State University
  Presenting Author