Enhancing the CS1 student experience with gamification

BackgroundIt is well established in the literature that active learning instruction in introductory STEM courses results in many desired student outcomes. Yet, regular use of high-quality active learning is not the norm in many STEM departments. Using results of a national survey, we identified 16 departments where multiple instructors reported using high levels of active learning in their introductory chemistry, mathematics, or physics courses. We conducted interviews with 27 instructors in these 16 departments to better understand the characteristics of such departments.ResultsUsing grounded theory methodology, we developed a model that highlights relevant characteristics of departments with high use of active learning instruction in their introductory courses. According to this model, there are four main, interconnected characteristics of such departments: motivated people, knowledge about active learning, opportunities, and cultures and structures that support active learning. These departments have one or more people who are motivated to promote the use of active learning. These motivated people have knowledge about active learning as well as access to opportunities to promote the use of active learning. Finally, these departments have cultures and structures that support the use of active learning. In these departments, there is a positive feedback loop that works iteratively over time, where motivated people shape cultures/structures and these cultures/structures in turn increase the number and level of commitment of the motivated people. A second positive feedback loop was found between the positive outcome of using active learning instruction and the strengthening of cultures/structures supportive of active learning.ConclusionsAccording to the model, there are two main take-away messages for those interested in promoting the use of active learning. The first is that all four components of the model are important. A weak or missing component may limit the desired outcome. The second is that desired outcomes are obtained and strengthened over time through two positive feedback loops. Thus, there is a temporal aspect to change. In all of the departments that were part of our study, the changes took at minimum several years to enact. While our model was developed using only high-use of active learning departments and future work is needed to develop the model into a full change theory, our results do suggest that change efforts may be made more effective by increasing the robustness of the four components and the connections between them.

In a previous study, we investigated a framework for teaching abstraction in computer science (CS) in the context of an introductory CS course for 7th-grade students. The framework was found effective for developing CS abstraction skills. In this paper, we describe a study that investigated teaching abstraction in CS to 7th-grade students through the perspective of gender. Specifically, we compared the CS abstraction abilities of boys and girls taking the introductory CS course in 7th grade (using the Scratch environment). We also examined the difference in the effect of the teaching strategy on CS abstraction abilities between boys and girls. Our findings show a significant advantage of girls over boys regarding several aspects of CS abstraction. We also found that the framework for teaching CS abstraction, which was already established in our previous study as effective in the context of an introductory course for 7th-grade students, has an enhanced effect in this context when it comes to girls. This enhancement was manifested by a better overall performance by the girls, when comparing boys and girls that took an introductory CS course in which this framework was used. It was also manifested by the girls' deeper and more reliable perception of CS. We conjecture that this framework has the potential to affect girls' self-efficacy, and as a result to create a positive effect by encouraging and motivating girls to pursue CS education beyond this introductory course. That is, this framework has the potential to contribute to solving the issue of underrepresentation of females at the different stages of CS education, or in other words, to widening the CS pipeline for females.

Full Paper. Research. We discuss possible ways to direct students to right level of introductory programming. While many schools offer college preparatory or advanced placement courses in computing, there is still, unfortunately, a large part of the college-ready population that has no opportunity to learn computing at all before they arrive. Regulation of CS education at the state/province or national level is still rare (but growing). Thus incoming students possess a wide range of skills and knowledge. When coupled with increasing enrollments, this diversity of experience can result in courses having large numbers of both absolute beginners and seasoned coders. Such courses are difficult to teach, intimidate novice students, and bore those with more experience. This can result in low engagement and retention.Unlike mathematics and language arts, introductory courses in CS vary widely from one institution to another in both conceptual material and programming language used. A standard point of entry to college mathematics is a calculus course, with some students instead starting earlier with pre-calculus or an algebra refresher, and others starting out in the second-term calculus course. There is rarely a concern about student skill being hidden by notational or other language differences, because the language of mathematics is close to universal. Similarly, freshman language arts courses in reading and/or writing assume a certain level of skill and maturity of comprehension and expressiveness in the target language; otherwise remedial courses are provided.We investigate placement of incoming first year students into appropriate introductory computer science courses at higher education institutions where there is more than one choice of first course. The goal is to determine the best way to decide which first course would be the most helpful for each student.

The pipeline of three introductory computer science courses at our university have low pass rates. As part of our efforts to improve the pass rates in these courses, we examine the students' mathematics preparation and their progress from one course to the next. We find that the minority of students who enter the university with good mathematics preparation are likely to succeed in our introductory computer science courses. For the majority of students, we suggest a series of interventions throughout the pipeline. Prior to taking Computer Science 1, students could gain more experience with problem solving during the Introduction to Computer Science and Introduction to Computer Engineering courses. We suggest adding precalculus as a prerequisite for Computer Science 2. For students who do not earn an A in Computer Science 2, we plan to examine whether taking a class in a second programming language before taking Computer Science 3 will improve performance in Computer Science 3. Our goal is to improve student learning and retention through these efforts, combined with continual innovation in the classroom.

ABSTRACTBackground and Context: The relationship between novices’ first programming language and their future achievement has drawn increasing interest owing to recent efforts to expand K–12 computing education. This article contributes to this topic by analyzing data from a retrospective study of more than 10,000 undergraduates enrolled in introductory computer science courses at 118 U.S. institutions of higher education.Objective: We explored the relationship between students’ first programming languages and both their final grades in an introductory computer science course and their attitudes about programming.Method: Multiple matching techniques compared those whose first language was graphical (e.g., Scratch), textual (e.g., Java), or absent prior to college.Findings: Having any prior programming experience had positive effects on both attitudes about programming and grades in introductory computer science courses. Importantly, students whose first language was graphical had higher grades than did students whose first language was textual, when the languages were introduced in or before early adolescent years.Implications: Learning any computer language is better than learning none. If programming is to be taught to students before early adolescence, it is advised to start with a graphical language. Future work should investigate the transition between different types of programming languages.

BackgroundWith the increased attention on the need to retain students within STEM majors, it is important for STEM instructors to adopt evidence-based instructional practices that are student-centric and employ active learning techniques. However, traditional approaches for increasing student-centric, active learning practices such as workshops, seminars, and department or college mandates have been either inefficient or ineffective at motivating institutional change. This is particularly true for introductory STEM courses with large enrollments. One promising approach is to develop and support instructors in forming communities of practice around reforming introductory and foundational STEM courses. By engaging instructors within these communities of practice, and connecting the communities with each other, instructors may be more likely to experience an epistemological shift that will lead to adoption of active learning practices.To explore whether participating in a community of practice is related to the use of student-centered, active learning techniques, 25 undergraduate foundational STEM courses whose instructors were members of a community of practice were observed using the Classroom Observation Protocol for Undergraduate STEM Courses. The results were compared to a sample of 35 undergraduate foundational STEM courses whose instructors were not members of a community of practice.ResultsInstructors who were members of a community of practice were much more likely to employ student-centric practices, such as asking questions, following up, and engaging in discussion, and much less likely to use instructor-centered practices, such as lecturing. In addition, students in these classes were more likely to be actively engaged in problem-solving activities rather than passively listening. We found that student-centric, active learning practices correlated with students attending and actively participating in class, an effect that is stronger for courses taught by instructors who were members of a community of practice.ConclusionCommunities of practice are a potentially effective mechanism for enhancing student learning and retention by increasing the use of active learning practices by STEM instructors. These communities are particularly effective when they consist of small, disciplinary teams working on the same course(s) and are linked with other individuals or groups that use evidence-based instructional practices.

Students in today's introductory Computer Science courses are often already experienced with sophisticated collaborative technologies and social computing systems. Among these popular systems are the online community building and information sharing sites that have become an intrinsic part of a new cyber-culture that continues to emerge. The involvement of students in collaborative technologies can be responsible in some cases for why certain students are inspired to pursue careers in computing disciplines. Yet very few CS 1 and CS 2 textbooks contain content related to collaborative software systems, presumably because of the extreme complexity involved in developing software that communicates with other software over a network. While social computing activities are very popular, the fact that it is not very prevalent in CS 1 and CS 2 course material can discourage students who have particular interest in that area of computing. In this paper, I present a system that I have developed that offers a simple way to incorporate class work and projects that involve collaborative networking and social computing paradigms at the level of introductory Computer Science courses.

This study investigated whether student academic achievement in college computer science programs in Taiwan could be predicted by factors reported to be effective in U.S. studies. Subjects were 940 college students enrolled in five universities offering computer science programs. A correlation study was conducted and prediction models were established. The predictive powers of college entrance examination (CEE) scores in relation to subsequent college performance appeared to be limited. Overall high school achievement and math course averages were identified as effective performance predictors. The close relationship between performance in introductory computer science courses and performance in complete computer science programs was validated. Significant linear prediction models with limited predictive powers were generated for overall performance but not for introductory computer science course performance. Model predictive powers were significantly improved when performance in introductory computer science courses was included in the models. No significant gender differences were found for CEE performance. However, female subjects outperformed male counterparts in course performance at both the high school and college levels.

Many colleges and universities offer an introductory computer science course based on a specific programming language. The Department of Computer Science at the University of Kansas has recently reorganized its introductory computer science course to include such topics as algorithms, top-down algorithmic design, elementary programming techniques, and introduction to time-sharing. Besides the discussion of this transition, the paper discusses a questionaire that was developed and utilized during this transition. It is hoped that others will benefit from our experiences.

The help-seeking interactions faculty encounter will vary depending upon the course structure and the students enrolled. While the course structure tends to remain the same, the students enrolled change each semester, presenting a new set of students who seek help in many different ways. We share our observations in investigating student behavior when using course resources, including office hours and online discussion forums, in two introductory computer science courses. Our goal is to explore differences in help-seeking behavior to construct Student "Help-Seeking" Personas. Preliminary analysis has shown that, for these two introductory CS courses, there are no well-defined personas that emerge from the grouping of help-seeking behaviors. The demographic of students exhibiting various help-seeking behaviors tends to be a near-proportionate subset of the overall course demographic. Thus, no distinct personas emerge from the students' help-seeking behaviors in introductory CS courses that faculty can utilize to better understand their students.

BackgroundPeer-cooperative learning has been shown in the literature to improve student success in gateway science and mathematics courses. Such studies typically demonstrate the impact of students’ attending peer-led learning sessions on their learning or grades in an individual course. In this article, we examine the effects of introducing a required, comprehensive peer-cooperative learning system across five departments simultaneously at a master’s public university, looking not only at students’ success in supported classes, but also their retention within STEM fields two years hence. Combining institutional demographic data with students’ course grades and retention rates, we compare outcomes between 456 students who took their major’s introductory course in the two years prior to implementation of the program, and 552 students who did so after implementation.ResultsWhile these two student groups did not significantly differ in either their demographic profile or their SAT scores, the post-implementation group earned significantly higher grades in their introductory courses in each major, due largely to an erasure of the mediating effect of SAT scores on course grades. Further, this increase in introductory course grades was also associated with an increase in the two-year retention rate of students in STEM majors.ConclusionsThis finding is significant as it suggests that implementing comprehensive educational reform using required peer-led cooperative learning may have the proximate effect of mitigating differences in academic preparation (as measured by SAT scores) for students in introductory STEM courses. Furthermore, this increase in success leads to increased retention rates in STEM, expanding the pipeline of students retained in such fields.

Introductory computer science courses offer an excellent test bed for utilizing a personalized system of instruction. The ubiquity and operating hours of computer terminals and computer centers in educational institutions is ideal for student self-pacing. The rapid response time of computers is a positive reinforcement when solving problems. The recent advent of the PLATO computer-based educational system provides many opportunities for students and faculty in computer science and many other disciplines. PLATO terminals provide a powerful motivational tool for PSI. Motivation is a critical part of computer science courses. Students are expected to acquire synthesis-level skills in the cognitive domain. This level of knowledge is higher than the level of skill, memorization or rule application, required for many other introductory courses. An Excellent Mixture for PSI: Computer Science, PLATO, and Knowledge Levels.

There are numerous ways to evaluate student programming ability, all of which have benefits and drawbacks. In this paper we discuss how we have combined a number of those evaluation techniques to assess student programming ability in an introductory computer science course and statistically analyze the relationships of student performance using the different evaluation techniques.

The enrollment in introductory computer science courses has been growing steadily for the last couple of years. Interest in the field is exploding across the nation. Colleges and universities of all shapes and sizes have seen enrollment in introductory computer science courses and to some extent in upper-division electives explode as well. Most R1 institutions handle such growth through the use of graduate TAs to teach CS1 courses. Many primarily undergraduate and/or liberal arts institutions don't have these resources, however. Complicating the scenario further, students coming to these non-research institutions expect personal interaction, are from a growingly diverse set of high-school graduates and seem to be less prepared for college than ever. Given the current funding climate for higher education, it is difficult to imagine how most universities and colleges will be able to negotiate this scenario. This BOF will provide a platform to discuss how to handle the growing, diverse, and uninitiated CS1 enrollment from many perspectives - individual, departmental, and institutional. What creative solutions can be brought to improve institutional motivation and how do we ensure that traditionally under-represented groups don't get left behind in the onslaught?

We look at the essential thinking skills students need to learn in the introductory computer science course based on object-oriented programming. We create a framework for such a course based on the elementary programming and design patterns. Some of these patterns are known in the pattern community, others enrich the collection. Our goal is to help students focus on mastering reasoning and design skills before the language idiosynchracies muddy the water.