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  1. This paper describes the beginning of a design-based research project for integrating computing activities in preservice teacher programs throughout a middle and secondary education department. Computing integration activities use computing tools, like programming, to support learning in non-computing disciplines. The paper begins with the motivation for integrating computing that encouraged widespread buy-in, design goals, and design parameters. The primary motivating factor for this work was preparing teachers to use technology to support learning in their classrooms. Involving computing education faculty in the preparation enabled the activities to include computer science and spread computational literacy. The paper also describes the process and year-long timeline for designing and implementing the integrations, followed by the details of the computing integrated activities. Last, the paper describes preservice teachers’ reactions to computing integration, focusing on before-and-after perceptions and knowledge of computing. Preservice teachers perceptions and knowledge of computing evolved similarly to teachers who engage in different approaches to learning about integrated computing, such as in elective or educational technology courses, suggesting that this approach is effective for engaging all teachers in integrating computing. In particular, the common feature that ignited teachers’ excitement about integrating computing was offering new opportunities to improve student learning and providing engaging activities within their non-computing discipline. 
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  2. null (Ed.)
    The subgoal learning framework has improved performance for novice programmers in higher education, but it has only started to be applied and studied in K-12 (primary/secondary). Programming education in K-12 is growing, and many international initiatives are attempting to increase participation, including curricular initiatives like Computer Science Principles and non-profit organizations like Given that subgoal learning is designed to help students with no prior knowledge, we designed and implemented subgoals in the introduction to programming unit in's Computer Science Principles course. The redesigned unit includes subgoal-oriented instruction and subgoal-themed pre-written comments that students could add to their programming activities. To evaluate efficacy, we compared behaviors and performance of students who received the redesigned subgoal unit to those receiving the original unit. We found that students who learned with subgoals performed better on problem-solving questions but not knowledge-based questions and wrote more in open-ended response questions, including a practice Performance Task for the AP exam. Moreover, at least one-third of subgoal students continued to use the subgoal comments after the subgoal-oriented instruction had been faded, suggesting that they found them useful. Survey data from the teachers suggested that students who struggled with the concepts found the subgoals most useful. Implications for future designs are discussed. 
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  3. This work extends previous research on subgoal labeled instructions by examining their effect across a semester-long, Java-based CS1 course. Across four quizzes, students were asked to explain in plain English the process that they would use to solve a programming problem. In this mixed methods study, we used the SOLO taxonomy to categorize student responses about problem-solving processes and compare students who learned with subgoal labels to those who did not. The use of the SOLO taxonomy classification allows us to look deeper than the mere correctness of answers to focus on the quality of the answers produced in terms of completeness of relevant concepts and explanation of relationships among concepts. Students who learned with subgoals produced higher-rated answers in terms of complexity and quality on three of four quizzes. Also, they were three times more likely to discuss issues of data type on a question about assignments and expressions than students who did not learn with subgoal labeling. This suggests that the use of subgoal labeling enabled students to gain a deeper and more complex understanding of the material presented in the course. 
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  4. Subgoal learning has improved student problem-solving performance in programming, but it has been tested for only one-to-two hours of instruction at a time. Our work pioneers implementing subgoal learning throughout an entire introductory programming course. In this paper we discuss the protocol that we used to identify subgoals for core programming procedures, present the subgoal labels created for the course, and outline the subgoal-labeled instructional materials that were designed for a Java-based course. To examine the effect of subgoal labeled materials on student performance in the course, we compared quiz and exam grades between students who learned using subgoal labels and those who learned using conventional materials. Initial results indicate that learning with subgoals improves performance on early applications of concepts. Moreover, variance in performance was lower and persistence in the course was higher for students who learned with subgoals compared to those who learned with conventional materials, suggesting that learning with subgoal labels may uniquely benefit students who would normally receive low grades or dropout of the course. 
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  5. There have been many calls recently for computing for all across the nation. While there are many opportunities to study and use computing to advance the fields of computer science, software development, and information technology, computing is also needed in a wide range of other disciplines, including engineering. Most engineering programs require students take a course that teaches them introductory programming, which covers many of the same topics as an introductory course for computing majors (and at times may be the same course). However, statistics about the success of a course that is an introductory programming course are sobering; approximately half the students will fail, forcing them to either repeat the course or leave their chosen field of study if passing the course is required. This NSF IUSE project incorporates instructional techniques identified through educational psychology research as effective ways to improve student learning and retention in introductory programming. The research team has developed worked examples of problems that incorporate subgoal labels, which are explanations that describe the function of steps in the problem solution to the learner and highlight the problem-solving process. Using subgoal labels within worked examples, which has been effective in other STEM fields, students are able to see an expert's problem solving process, which helps students learn to solving problems before they can solve problem themselves. Experts, including instructors, teaching introductory level courses are often unable to explain the process they use in problem solving at a level that learners can grasp because they have automated much of the problem-solving processes after many years of practice. This submission will present the results of the first part of development of subgoals and will explain how to integrate them into classroom lessons in introductory computing classes. 
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  6. null (Ed.)
    A recent study about the effectiveness of subgoal labeling in an introductory computer science programming course both supported previous research and produced some puzzling results. In this study, we replicate the experiment with a different student population to determine if the results are repeatable. We also gave the experimental task to students in a follow-on course to explore if they had indeed mastered the programming concept. We found that the previous puzzling results were repeated. In addition, for the novice programmers, we found a statistically significant difference in performance based on whether the student had previous programming courses in high school. However, this performance difference disappears in a follow-on course after all students have taken an introductory computer science programming course. The results of this study have implications for how quickly students are evaluated for mastery of knowledge and how we group students in introductory programming courses. 
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