This research employs the fuzzy-set qualitative comparative analysis (fsQCA) method to investigate the configurations of multiple factors influencing scientific concept learning, including augmented reality (AR) technology, the concept map (CM) strategy and individual differences (eg, prior knowledge, experience and attitudes). A quasi-experiment was conducted with 194 seventh-grade students divided into four groups: AR and CM (N = 52), AR and non-CM (N = 51), non-AR and CM (N = 40), non-AR and non-CM (N = 51). These students participated in a science lesson on 'The structure of peach blossom'. This study represents students' science learning outcomes by measuring their academic performance and cognitive load. The fsQCA results reveal that: (1) factors influencing students' academic performance and cognitive load are interdependent, and a single factor cannot constitute a necessary condition for learning outcomes; (2) multiple pathways can lead to the same learning outcome, challenging the notion of a singular best path derived from traditional analysis methods; (3) the configurations of good and poor learning outcomes exhibit asymmetry. For example, high prior knowledge exists in both configurations leading to good and poor learning outcomes, depending on how other conditions are combined.