In programming, the concept of variables is central to learning other concepts like loops, functions, and conditions, and the way variables are explained influences students' understanding. Prior work observed Massive Open Online Courses (MOOCs) on introductory programming to investigate how the topic is addressed in teaching materials. Our work aims to verify if their results generalize to other materials by analyzing 13 popular Scratch and Python programming books and investigating (1) which definitions and analogies are currently being used to explain the variables, (2) looking into the programming concepts that are introduced alongside variables, and (3) analyzing if and how variable naming practices are introduced. Our results support previous findings from MOOCs, suggesting that CS educators and developers of educational materials for introductory programming could pay more attention to how they explain variables and can be more deliberate and consistent when it concerns the teaching of naming practices. Additionally, we found specific analogies used to explain variables, and differences between programming languages in the order that variables are introduced. Our work can be used to update current educational materials and inform the development of new ones.

Motivation. Code reading skills are important for comprehension. Explain-in-plain-English tasks (EiPE) are one type of reading exercises that show promising results on the ability of such exercises to differentiate between particular levels of code comprehension. Code reading/explaining skills also correlate with code writing skills. Objective. This paper aims to provide insight in what novice students express in their explanations after reading a piece of code, and what these insights can tell us about how the students comprehend code. Method. We performed an exploratory analysis on four reading assignments extracted from a university-level beginners course in Python programming. We paid specific attention to 1) the core focus of student answers, 2) elements of the code that are often included or omitted, and 3) errors and misconceptions students may present. Results. We found that students prioritize the output that is generated by print-statements in a program. This is indication that these statements may have the ability to aid students make sense of code. Furthermore, students appear to be selective about which elements they find important in their explanation. Assigning variables and asking input was less often included, whereas control-flow elements, print statements and function definitions were more often included. Finally, students were easily confused or distracted by lines of code that seemed to interfere with the newly learned programming constructs. Also domain knowledge (outside of programming) both positively and negatively interfered with reading and interpreting the code. Discussion. Our results pave the way towards a better understanding of how students understand code by reading and of how an exercise containing self-explanations after reading, as a teaching instrument, may be useful to both teachers and students in programming education.