Knowledge components (KCs) have many applications. In computing education, knowing the demonstration of specific KCs has been challenging. This paper introduces an entirely data-driven approach for: (1) discovering KCs; and (2) demonstrating KCs, using students' actual code submissions. Our system is based on two expected properties of KCs: (1)…

Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts. Though many innovations have been made in KT, most models including the state-of-the-art Deep KT (DKT) mainly leverage each student's response either as correct or incorrect, ignoring its content. In…

In computer science education timely help seeking during large programming projects is essential for student success. Help-seeking in typical courses happens in office hours and through online forums. In this research, we analyze students coding activities and help requests to understand the interaction between these activities. We collected…

In colleges, programming is increasingly becoming a general education course of almost all STEM majors as well as some art majors, resulting in an emerging demand for scalable programming education. To support scalable education, teaching activities such as grading and feedback have to be automated. Recently, online judge systems have been…

Teamwork, often mediated by version control systems such as Git and Apache Subversion (SVN), is central to professional programming. As a consequence, many colleges are incorporating both collaboration and online development environments into their curricula even in introductory courses. In this research, we collected GitHub logs from two…

Is there a pattern in how students solve Parsons puzzles? Is there a difference between the puzzle-solving strategies of C++ and Java students? We used Markov transition matrix to answer these questions. We analyzed the solutions of introductory programming students solving Parsons puzzles involving if-else statements and while loops in C++ and…

Automatically identifying struggling students learning to program can assist teachers in providing timely and focused help. This work presents a new deep-learning language model for predicting "bug-fix-time", the expected duration between when a software bug occurs and the time it will be fixed by the student. Such information can guide…

In an Intelligent Tutoring System (ITS), problem (or question) difficulty is one of the most critical parameters, directly impacting problem design, test paper organization, result analysis, and even the fairness guarantee. However, it is very difficult to evaluate the problem difficulty by organized pre-tests or by expertise, because these…

As programming must be learned by doing, introductory programming course learners need to solve many problems, e.g., on systems such as 'Online Judges'. However, as such courses are often compulsory for non-Computer Science (nonCS) undergraduates, this may cause difficulties to learners that do not have the typical intrinsic motivation for…

Viewing worked examples before problem solving has been shown to improve learning efficiency in novice programming. Example-based feedback seeks to present smaller, adaptive worked example steps during problem solving. We present a method for automatically generating and selecting adaptive, example-based programming feedback using historical…

Recent years have seen a growing interest in block-based programming environments for computer science education. While these environments hold significant potential for novice programmers, they lack the adaptive support necessary to accommodate students exhibiting a wide range of initial capabilities and dispositions toward computing. A promising…

This paper characterized the extent of collaboration of pairs of novice programmers as they traced and debugged fragments of code using cross-recurrence quantification analysis (CRQA). This was a preliminary analysis that specifically aimed to compare and assess the collaboration of pairs consisting of two individuals who may have different or…

Intelligent Tutoring Systems (ITSs) have shown success in the domain of programming, in part by providing customized hints and feedback to students. However, many popular novice programming environments still lack these intelligent features. This is due in part to their use of open-ended programming assignments, which are difficult to support with…

The emergence of Massive Open Online Courses (MOOCs) has enabled new research to analyze typical behaviors of learners. In this paper, we investigate whether this research is generalizable to other courses that are backed by a learning management system (LMS) as MOOCs are. Building on methods developed by others, we characterize individual…

Early prediction of student difficulty during long-duration learning activities allows a tutoring system to intervene by providing needed support, such as a hint, or by alerting an instructor. To be effective, these predictions must come early and be highly accurate, but such predictions are difficult for open-ended programming problems. In this…