In personalized learning, each student gets a customized learning plan according to their pace of learning, instructional preferences, learning objects, etc. Hence the content recommender system in Personalized Learning Environment (PLE) should adapt to learner attributes and suggest appropriate learning resources to aid the learning process and improve the learning outcomes. This systematic literature review aims to analyze and summarize the studies on learning content recommenders in adaptive and personalized learning environments from 2015 to 2020. The publications were searched using proper keywords and filtered using the inclusion and exclusion criteria, which resulted in 52 publications. This paper summarizes the recent trends in research on different aspects of the recommender systems, such as learner attributes, recommendation methods, evaluation metrics, and the usability tests used by the researchers. It is observed that cognitive aspects of learners like learning style, preferences, knowledge level, etc., are used by most studies than non-cognitive aspects as social tags or trust. In most cases, recommendation engines are a hybrid of collaborative filtering, content-based filtering, ontological approaches, etc. All models were evaluated for the correctness of the prediction done, and a few studies have also done evaluations based on learner satisfaction or usability.

Identifying the set of cognitive processes (CPs) a student can go through during computer programming is an interesting research problem. It can provide a better understanding of the human aspects in computer programming process and can also contribute to the computer programming education in general. The study identified the presence of a set of 42 CPs in computer programming (C language). The study used Verbal Protocol Analysis (VPA) in identifying these CPs. It is a qualitative study on the Verbal Protocols (VPs) of 19 students. Some of the CPs have been inferred by referring to the literature and some have been additionally identified by this study. The additional CPs found are confusion, hypothesis, interrogation, iteration, monitoring, recollection, recurrence, and translation. It is observed that programming involves the interplay of lower and higher CPs and needs various cognitive skills, which increase the processing load on the brain and make the programming process difficult and complex to learn and practice. The same set of CPs was found in both the effective and ineffective subjects. The research results can provide deeper knowledge to teachers on cognitive aspects of programming and the cognitive behavior of students during the programming process.

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