Table 8. Learning focused research.
| Leaf node categories |
Brief description of major area of focus | Brief description of major findings | Articles |
|---|---|---|---|
| Individual | |||
| Programming | Severity of errors to identify learning difficulties. | Identification of difficult to fix errors to plan appropriate interventions. | McCall & Kölling, 2019 |
| Use of syntactically correct programs to automatically correct buggy programs. | Correction of errors in programs. | Bhatia, Kohli & Singh, 2018 | |
| Programming profiles to identify the aptitudes and skills. | Programming profiles helped instructors to guide students. | Chaweewan et al., 2018 | |
| Static analysis of students’ codes to find common occurring errors. | Identification of most frequent errors. | Delev & Gjorgjevikj, 2017 | |
| Scrutinizing the errors in students' programs. | Identification of missing competencies. | Berges et al., 2016 | |
| Identification of non-terminating code. | Indication of the problematic parts of the code. | Edwards, Shams & Estep, 2014 | |
| Parameters and techniques to analyze learning or predict performance. | Identification of programming parameters or techniques that effect students’ performance. | Lagus et al., 2018; Ninrutsirikun et al., 2020; Castro-Wunsch, Ahadi & Petersen, 2017; Ahadi, Hellas & Lister, 2017; Watson, Li & Godwin, 2014; Ahadi et al., 2015; Ashenafi, Riccardi & Ronchetti, 2015; Carter, Hundhausen & Adesope, 2015 | |
| Learning styles | Learning styles and their effect on outcomes. | Identification of learning styles that resulted in better outcomes. | Kumar, 2017 |
| The relationships of micro and macro learning patterns with final performance. | Patterns demonstrated better correlation for good performances. | Chung & Hsiao, 2020 | |
| Students’ engagements in course related activities, to predict performance. | Examined the features to predict students’ performance. | Premchaiswadi, Porouhan & Premchaiswadi, 2018 | |
| Learning process | Learning difficulties and their causes. | Identification of learning difficulties and their potential causes. | Simkins & Decker, 2016 |
| Genetic algorithm to identify personal learning needs. | Identification of personal learning needs of students. | Lin et al., 2018 | |
| Collaborative | |||
| Peer | Peer instruction for collaborative learning. | Established relationship between students’ performance and collaborative learning technique. | Liao et al., 2019 |
| Peer feedback on programming. | Positive effect on learning and students’ performance. | Azcona, Hsiao & Smeaton, 2018 | |
| Social | Social learning activities to predict students’ performances. | Cumulative activities reflected better accuracies than individual activities. | al-Rifaie, Yee-King & d’Inverno, 2017 |
| Social learning behavior along with the programming behavior for prediction. | Prediction accuracies improved with social learning behavior. | Carter, Hundhausen & Adesope, 2017 | |
| Collaborative learning environment that is based on exchanging comments among students. | Improvements in students’ performance. | Echeverría et al., 2017 | |