Efforts to improve computer science education are underway, and teachers of computer science are challenged in introductory programming courses to help learners develop their understanding of programming and computer science. Identifying and addressing students’ misconceptions is a key part of a computer science teacher's competence. However, relevant research on this topic is not as fully developed in the computer science education field as it is in mathematics and science education. In this article, we first review relevant literature on general definitions of misconceptions and studies about students’ misconceptions and other difficulties in introductory programming. Next, we investigate the factors that contribute to the difficulties. Finally, strategies and tools to address difficulties including misconceptions are discussed. Based on the review of literature, we found that students exhibit various misconceptions and other difficulties in syntactic knowledge, conceptual knowledge, and strategic knowledge. These difficulties experienced by students are related to many factors including unfamiliarity of syntax, natural language, math knowledge, inaccurate mental models, lack of strategies, programming environments, and teachers’ knowledge and instruction. However, many sources of students’ difficulties have connections with students’ prior knowledge. To better understand and address students’ misconceptions and other difficulties, various instructional approaches and tools have been developed. Nevertheless, the dissemination of these approaches and tools has been limited. Thus, first, we suggest enhancing the dissemination of existing tools and approaches and investigating their long-term effects. Second, we recommend that computing education research move beyond documenting misconceptions to address the development of students’ (mis)conceptions by integrating conceptual change theories. Third, we believe that developing and enhancing instructors’ pedagogical content knowledge (PCK), including their knowledge of students’ misconceptions and ability to apply effective instructional approaches and tools to address students’ difficulties, is vital to the success of teaching introductory programming.

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<p>The demand for computing professionals in the workplace has led to increased attention to computer science education, and introductory computer science courses have been introduced at different levels of education. This study investigated the relationship between gender, academic performance in non-programming subjects, and programming learning performance among middle school students with no prior programming experience who took an introductory programming course. We found that girls performed as well as or even better than boys in introductory programming among high-ability Chinese middle school students. However, we found that, instead of gender, students’ performance differences in programming were better explained by their academic performance in non-programming subjects. Students’ math ability was strongly related to their programming performance, and their English ability was the best predictor of their success in introductory programming for these Chinese students. Findings confirm previous studies that have shown a relationship between students’ math ability and performance in learning to program, but the relationship between English ability and introductory programming was unexpected. While this relationship may be specific to students whose first language is not English, aspects of native language may pose hidden barriers that might affect all students’ success in introductory programming.</p>

With the expansion of computer science (CS) education, CS teachers in K-12 schools should be cognizant of student misconceptions and be prepared to help students establish accurate understanding of computer science and programming. Digital tools, such as automated assessment systems, can be useful and supportive in teaching CS courses. This two-stage design-based research (DBR) study investigated the effects of targeted feedback in an automated assessment system for addressing common misconceptions of high school students in a Java-based introductory programming course. Based on students’ common errors and underlying misconceptions, targeted feedback messages were designed and provided for students. The quantitative analysis found that with targeted feedback students were more likely to correct the errors in their code. The qualitative analysis of students’ solutions revealed that when improving the code, students receiving feedback made fewer intermediate incorrect solutions. In other words, the targeted feedback messages may help to promote conceptual change and facilitate learning. Although the findings of this exploratory study showed evidence of the power of digital tools, more research is needed to make technology benefit more CS teachers.

A quality computer science (CS) teacher needs to understand students’ common misconceptions in learning CS. This study explored one aspect of CS teachers’ understanding of student misconceptions: their perceptions of student misconceptions related to introductory programming. Perceptions in this study included three parts: teachers’ perceived frequency of a student misconception, teachers’ perceived importance of a misconception in learning, and teachers’ confidence in addressing a misconception. Teachers in our study taught a Python-based CS course for high schools students. A survey was designed and administered to assess teachers’ perceptions of students’ misconceptions. Our results indicated that teachers’ confidence of addressing misconceptions and the teaching context may affect their perceptions of student misconceptions. We also found that some latent misconceptions are likely to lead to a perception of low frequency as they can be more difficult to detect. Moreover, our study found that teachers’ degrees and additional computing training showed positive relationships with their confidence of addressing student misconceptions and that additional computing training also showed a positive relationship with teachers’ perceived importance of student misconceptions. Implications of the findings for future research and practice of CS education are discussed.