Table 9. Tool focused studies.
| Leaf node categories | Brief description of major area of focus | Brief description of major findings | Articles |
|---|---|---|---|
| IDE | |||
| Web-based | Identification of anti-patterns in students’ programs. | Identification of patterns showing better outcomes. | Ureel & Wallace, 2019; Ureel & Wallace, 2015 |
| Detection of changes in programming behavior to find students who need special assistance in programming. | Identification of students who need additional support to learn programming. | Estey, Keuning & Coady, 2017 | |
| Effectiveness of web-based IDE. | Significant relationship between web-based programming tool and students' performance. | España-Boquera et al., 2017 | |
| Integration of students’ programming activities. | Helped in reducing students’ problems. | Edwards, Tilden & Allevato, 2014 | |
| Presence of non-terminating code through infinite loops. | Supported programming activities. | Edwards, Shams & Estep, 2014 | |
| Support | |||
| Visualization | Code analysis to visualize working progress. | The tool provided visual analysis of differences between the codes. | Heinonen et al., 2014 |
| Prediction | Peer programming feedback and adaptive learning to predict students’ performance. | The system was effective to support learning. | Azcona, Hsiao & Smeaton, 2018 |
| A Java grader system for performance prediction using machine learning algorithms. | The tool predicted performances by forecasting the final grades. | Koong et al., 2018 | |
| Feedback | Feedback by scrutinizing the students’ programs. | Auto- feedback on student codes to support learning. | Berges et al., 2016; Ureel & Wallace, 2019; Ureel & Wallace, 2015 |
| Feedback delivery of paper-based evaluation. | The system found effective in transmitting the feedback to students. | Hsiao, Huang & Murphy, 2017 | |
| Feedback through graphs by examining the code. | No major difference in students’ performances without interactions. | Seanosky et al., 2017 | |
| Personalized learning |
Scrutinizing the programming and learning behaviors to identify individual learning needs. | Supported students by recommending personalized learning material. | Fu et al., 2017 |
| Platform for self-paced learning. | Enhanced motivation for learning. | Su et al., 2015 | |
| A system to support, motivate, and guide students by online reviewing their work. | The tool supported the process of learning by optimizing the learning efforts. | Hijon-Neira et al., 2014 | |
| Analyzing the programming behaviors of students through tool interactions. | Identification of programming behaviors to design the personalized course activities. | Pereira et al., 2020 | |