👨‍🌾Exercise

A systematic literature review is a rigorous and transparent method of summarizing and synthesizing the existing research on a specific topic or question in computer science. It can help you to identify, appraise, and compare the relevant studies, and to draw conclusions and implications from them.

There are many steps involved in conducting a systematic literature review, such as defining the research question, developing the search strategy, screening and selecting the studies, extracting and analyzing the data, and reporting the results. To practice these skills, you can try some of the following exercises:

• Exercise 1: Formulate a clear and focused research question for a systematic literature review in computer science, using the PICO or PEO framework. PICO stands for Population, Intervention, Comparison, and Outcome, while PEO stands for Population, Exposure, and Outcome. These frameworks can help you to specify the key elements of your question and to guide your search strategy. For example, a PICO question could be: What is the effect of gamification on students’ motivation and learning outcomes in computer science education? A PEO question could be: How do gender and prior knowledge interact with students’ performance and attitudes in computer science courses?

• Exercise 2: Develop a comprehensive and systematic search strategy for your research question, using appropriate keywords, synonyms, Boolean operators, and filters. You can use online databases such as ACM Digital Library, IEEE Xplore, or Scopus to search for relevant studies. You can also use tools such as Polyglot1 to translate your search query from one database to another. For example, a search strategy for the PICO question above could be: (gamification OR game-based learning) AND (motivation OR engagement OR satisfaction) AND (learning outcomes OR achievement OR performance) AND (computer science OR programming OR coding) AND (education OR teaching OR learning).

• Exercise 3: Screen and select the studies that meet your inclusion and exclusion criteria, based on their titles, abstracts, and full texts. You can use tools such as Deduplication2 to remove duplicate references from your search results. You can also use tools such as Hotkey3 to assign keyboard shortcuts to common actions in EndNote, such as marking references as included or excluded, adding notes, or moving references to different groups. For example, you can include studies that are published in English, that have an experimental or quasi-experimental design, and that measure the effect of gamification on students’ motivation and learning outcomes in computer science education. You can exclude studies that are not relevant to your question, that have a low quality or high risk of bias, or that have missing or incomplete data.

• Exercise 4: Extract and analyze the data from the selected studies, using a standardized data extraction form or a software tool. You can use tools such as Covidence or Rayyan to facilitate the data extraction and analysis process. You can also use tools such as RevMan or R to perform a meta-analysis, which is a statistical method that combines and summarizes the data from the selected studies. For example, you can extract and analyze the data on the characteristics of the participants, the type and duration of the gamification intervention, the type and measurement of the motivation and learning outcomes, and the effect size and confidence interval of the intervention effect.

• Exercise 5: Report the results of your systematic literature review, using a clear and structured format and following the PRISMA guidelines. PRISMA stands for Preferred Reporting Items for Systematic Reviews and Meta-Analyses, and it is a widely used standard for conducting and reporting systematic reviews in computer science. You can use the PRISMA checklist and flow diagram to ensure that you include all the essential information in your report. For example, you can report the background, objectives, methods, results, discussion, and conclusions of your systematic literature review, as well as the limitations, implications, and recommendations for future research.

I hope these exercises are helpful for you to practice and improve your skills in systematic literature review in computer science. If you need more guidance or resources, you can check out some of the websites that I found for you using my search web tool4.