Search engines are great allies in our daily educational tasks. However, usually, these tools are prepared only for factual learning and are less effective when dealing with more complex learning tasks. Thus, in recent years, Searching as Learning (SAL) research area has been developing from proposals that target the main challenges involving learning during the search process. The effectiveness of educational technologies in providing appropriate instructions depends directly on the input information. Gathering information on what should be taken into account in a search as a learning process can support the development of specialized search engines to support learning. Therefore, we performed a systematic mapping of the literature in order to gather this information, raising the dimensions and their associated variables.

Current search engines are not designed to facilitate learning as they do not lead the user to develop more complex skills. Searching as Learning (SAL) emerged as a research area from the intersection of information search and learning technologies in order to advance the study of searching as a learning process. However, we wonder how have the learning theories and approaches been explored in SAL. Through a systematic review of the literature, we identified 65 papers that report SAL solutions. We analyzed them, seeking to answer (i) which learning theories, approaches and methods support the searching as a learning process, and (ii) what metrics, procedures, or treatments were used to measure learning during the searching process. We uncover the learning perspective in the SAL literature, discussing the learning paradigms, the mechanisms influencing the learning process, the search session design for learning and the knowledge gain measurement strategies.

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