Using response system through voting in peer instruction for learning sustainability

Sustainable education must employ strategies that promote lifelong and meaningful learning. Peer Instruction (PI) is an active learning pedagogy specifically designed to achieve this. There are a number of elements involved in the various steps of the PI pedagogy which contributes to its effectiveness. However, most research studies reported in Peer Instruction focused on its use in science education and mainly on the whole pedagogy. The significance of the individual elements of the model have not been fully explored. Reports are also scarce on the use and benefits of PI in non-science classrooms. This study evaluates the pedagogical benefits of one of the elements of the PI model; the use of automated feedback based on students’ voting. 42 students in a postgraduate teacher education class were taken through sessions of Peer Instruction and traditional lectures; learning outcomes were compared in terms of student performance and student engagement and motivation. Performance tests (pre-tests and post-tests), live classroom observations and students’ reflections were monitored to determine the level of performance and engagement. Results show that students reported increased interest, motivation and engagement and the ability of the voting sessions to foster metacognition. Active learning and learning readiness were also emphasized while the lecture sessions were reported as normal or usual. The result validates the usefulness of voting component of the PI model for fostering improved learning; noting that students are able to benefit more from personal evaluation when voting results are displayed after voting

Why Not Robot Teachers: Artificial Intelligence for Addressing Teacher Shortage

Global teacher shortage is a serious concern with grave implications for the future of education. This calls for novel ways of addressing teacher roles. The economic benefits of tireless labor inspires the need for teachers who are unlimited by natural human demands, highlighting consideration for the affordances of robotics and Artificial Intelligence in Education (AIED) as currently obtainable in other areas of human life. This however demands designing robotic personalities that can take on independent teacher roles despite strong opinions that robots will not be able to fully replace humans in the classroom of the future. In this article, we argue for a future classroom with independent robot teachers, highlighting the minimum capabilities required of such personalities in terms of personality, instructional delivery, social interaction, and affect. We describe our project on the design of a robot teacher based on these. Possible directions for future system development and studies are highlighted