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Experiential learning (ExL) is the process of learning through experience ormore specifically "learning through reflection on doing". In this paper, wepropose a simulation of these experiences, in Augmented Reality (AR),addressing the problem of language learning. Such systems provide an excellentsetting to support "adaptive guidance", in a digital form, within a realenvironment. Adaptive guidance allows the instructions and learning content tobe customised for the individual learner, thus creating a unique learningexperience. We developed an adaptive guidance AR system for language learning,we call Arigat\=o (Augmented Reality Instructional Guidance & TailoredOmniverse), which offers immediate assistance, resources specific to thelearner's needs, manipulation of these resources, and relevant feedback.Considering guidance, we employ this prototype to investigate the effect of theamount of guidance (fixed vs. adaptive-amount) and the type of guidance (fixedvs. adaptive-associations) on the engagement and consequently the learningoutcomes of language learning in an AR environment. The results for the amountof guidance show that compared to the adaptive-amount, the fixed-amount ofguidance group scored better in the immediate and delayed (after 7 days) recalltests. However, this group also invested a significantly higher mental effortto complete the task. The results for the type of guidance show that theadaptive-associations group outperforms the fixed-associations group in theimmediate, delayed (after 7 days) recall tests, and learning efficiency. Theadaptive-associations group also showed significantly lower mental effort andspent less time to complete the task.

Arigat\=o: Effects of Adaptive Guidance on Engagement and Performance in Augmented Reality Learning Environments