Narrated animated solution videos in a mastery setting

In the context of a generic harmonic oscillator, we investigated students' accuracy in determining the period, frequency, and angular frequency from mathematical and graphical representations. In a series of studies including interviews, free response tests, and multiple choice tests developed in an iterative process, we assessed students in both algebra-based and calculus-based, traditionally instructed university-level introductory physics courses. Using the results, we categorized nine skills necessary for proficiency in determining period, frequency, and angular frequency. Overall results reveal that, postinstruction, proficiency is quite low: only about 20%-40% of students mastered most of the nine skills. Next, we used a semiquantitative, intuitive method to investigate the hierarchical structure of the nine skills. We also employed the more formal item tree analysis method to verify this structure and found that the skills form a multilevel, nonlinear hierarchy, with mastery of some skills being prerequisite for mastery in other skills. Finally, we implemented a targeted, 30-min group-work activity to improve proficiency in these skills and found a 1 standard deviation gain in accuracy. Overall, the results suggest that many students currently lack these essential skills, targeted practice may lead to required mastery, and that the observed hierarchical structure in the skills suggests that instruction should especially attend to the skills lower in the hierarchy.

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“…Refs. [14,15]). Such practice could increase the fluency and retention of these skills and help students to solve more complex problems.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

“…Given the relatively simple nature of these procedural skills, it is possible that only brief, targeted instruction is needed for significant improvements in proficiency (e.g., see Refs. [14,15]).…”

Section: Introductionmentioning

confidence: 99%

Observed hierarchy of student proficiency with period, frequency, and angular frequency

Young

Heckler

2018

Phys. Rev. Phys. Educ. Res.

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“…These results are helpful not only in the specific domain of the STEM essential skill of vector math, but also in providing evidence and arguments for a more general framework to guide the design of computer-based training with simple feedback in similar domains. Note that while this study investigates factors effecting learning of a simple and essential procedure skill for physics, there have been other relatively recent lab studies in the physics education domain for improving student knowledge of specific topics [39,40] and conceptual reasoning in problem solving [41] that also show promise for application in a course.…”

Section: Summary and General Discussionmentioning

confidence: 99%

Factors affecting learning of vector math from computer-based practice: Feedback complexity and prior knowledge

Heckler

Mikula

2016

Phys. Rev. Phys. Educ. Res.

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In experiments including over 450 university-level students, we studied the effectiveness and time efficiency of several levels of feedback complexity in simple, computer-based training utilizing static question sequences. The learning domain was simple vector math, an essential skill in introductory physics. In a unique full factorial design, we studied the relative effects of "knowledge of correct response" feedback and "elaborated feedback" (i.e., a general explanation) both separately and together. A number of other factors were analyzed, including training time, physics course grade, prior knowledge of vector math, and student beliefs about both their proficiency in and the importance of vector math. We hypothesize a simple model predicting how the effectiveness of feedback depends on prior knowledge, and the results confirm this knowledge-by-treatment interaction. Most notably, elaborated feedback is the most effective feedback, especially for students with low prior knowledge and low course grade. In contrast, knowledge of correct response feedback was less effective for low-performing students, and including both kinds of feedback did not significantly improve performance compared to elaborated feedback alone. Further, while elaborated feedback resulted in higher scores, the learning rate was at best only marginally higher because the training time was slightly longer. Training time data revealed that students spent significantly more time on the elaborated feedback after answering a training question incorrectly. Finally, we found that training improved student self-reported proficiency and that belief in the importance of the learned domain improved the effectiveness of training. Overall, we found that computer based training with static question sequences and immediate elaborated feedback in the form of simple and general explanations can be an effective way to improve student performance on a physics essential skill, especially for less prepared and low-performing students.

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“…Recently, Schroeder et al [9] and Gladdening et al [10] have implemented something more similar to our work and focus, namely, computer-based mastery practice of specific skills in an education research lab setting and have shown it to be effective. The target skills in their studies tended to be specific to a particular physics problem type and subtopic (e.g., electric fields and potential for plane and spherical symmetries) and the studies focused on accuracy, while our target skills tend to be more broadly applicable (though not limited to this) and, as we will discuss below, we are aiming at accuracy, fluency, and retention.…”

Section: Introductionmentioning

confidence: 94%

Framework and implementation for improving physics essential skills via computer-based practice: Vector math

Mikula

Heckler

2017

Phys. Rev. Phys. Educ. Res.

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We propose a framework for improving accuracy, fluency, and retention of basic skills essential for solving problems relevant to STEM introductory courses, and implement the framework for the case of basic vector math skills over several semesters in an introductory physics course. Using an iterative development process, the framework begins with a careful identification of target skills and the study of specific student difficulties with these skills. It then employs computer-based instruction, immediate feedback, mastery grading, and well-researched principles from cognitive psychology such as interleaved training sequences and distributed practice. We implemented this with more than 1500 students over 2 semesters. Students completed the mastery practice for an average of about 13 min =week, for a total of about 2-3 h for the whole semester. Results reveal large (>1 SD) pretest to post-test gains in accuracy in vector skills, even compared to a control group, and these gains were retained at least 2 months after practice. We also find evidence of improved fluency, student satisfaction, and that awarding regular course credit results in higher participation and higher learning gains than awarding extra credit. In all, we find that simple computer-based mastery practice is an effective and efficient way to improve a set of basic and essential skills for introductory physics.

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Narrated animated solution videos in a mastery setting

Cited by 16 publications

References 32 publications

Observed hierarchy of student proficiency with period, frequency, and angular frequency

Observed hierarchy of student proficiency with period, frequency, and angular frequency

Factors affecting learning of vector math from computer-based practice: Feedback complexity and prior knowledge

Framework and implementation for improving physics essential skills via computer-based practice: Vector math

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