Investigating children's deep learning of the tree life cycle using mobile technologies

This study investigates children's problem-solving activities during mobile learning in an outdoor summer camp setting. We designed a mobile application to support children on trails at a nature center to apply strategies for decision making about tree life cycles. We analyzed video records of 10 groups (9 dyads and 1 triad) of children (ages 9–12) using primarily a thematic qualitative analysis of learning episodes. We analyzed how children used problem-solving strategies to identify and capture the tree cycle with the help of mobile tablets. We found that our mobile learning experience and its external representations supported the following: (1) engagement in deep learning in the natural setting as evidenced by coordinating decisions with photographic evidence; (2) use of procedural or tactical strategies to approach the problem; and (3) use of real-time decision making strategies about tree life cycles. •The mobile application was designed to support children learning about trees at a nature center.•We investigated children's problem-solving strategies to identify and capture the stages of the tree cycle.•With the external representation provided by mobile tablets, children engaged in deep science learning in an outdoor setting.