Systematically reviewing the potential of concept mapping technologies to promote self-regulated learning in primary and secondary science education

We systematically searched five databases to assess the potential of concept mapping-based technologies to promote self-regulated learning in science education. Our search uncovered 17 relevant studies that investigated seven different types of learning technologies. We performed a narrative analysis assessing how each technology affects self-regulated learning through cognitive, metacognitive, and motivation strategies, according to Schraw et al. (2006)'s model. We suggest concept mapping technologies may affect self-regulated learning through enhancing these strategies to varying degrees. Computer software was particularly useful for developing cognitive strategies through ease of use. Teaching agents were particularly useful for developing metacognitive strategies by coupling visualisation of knowledge patterns with performance monitoring, aided by a teaching metaphor. Finally, mobile devices and teaching agents were most effective in enhancing motivation. Effects on knowledge gains remain unclear due to small sample sizes.