Seattle, Washington
June 14, 2015
June 14, 2015
June 17, 2015
978-0-692-50180-1
2153-5965
Mathematics
10
26.1669.1 - 26.1669.10
10.18260/p.25005
https://peer.asee.org/25005
407
Christine Lindstrøm works as an Associate Professor of Science in the Faculty of Teacher Education at Oslo and Akershus University College in Oslo, Norway, where she teaches physics and science education to pre-service science teachers. She undertook her tertiary studies at the University of Sydney, Australia, from which she has a Bachelor of Science (Honours), Master of Education and PhD in Physics. Christine’s PhD project was in Physics Education Research, where she focused on improving the first year physics course by developing and implementing ‘Link Maps’, as well as synthesising an understanding of physics student learning by integrating a variety of theoretical backgrounds, from neuroscience via cognitive psychology to educational theories. Christine’s current research focuses on improving the science teacher education program at Oslo and Akershus University College, and she has a keen interest in how the brain learns physics. Christine also holds a position as Adjunct Associate Professor of University Pedagogy at the Norwegian University of Science and Technology, where she teaches short courses on university teaching to PhD students and researchers.
Using Khan Academy to support students' mathematical skill development in a physics courseThis paper reports on a pilot study of using a free online mathematics learning tool, Khan Academy(KA), to strengthen the relevant mathematics skills of pre-service year 1-10 science teachers in theirintroductory physics course at a large teacher education institution in Norway. By guiding thestudents to the relevant topics in KA before each physics class, the goal was to improve students’mathematics skills by motivating them to spend more time working on mathematics and byworking with a pedagogically well-designed mathematics learning tool.This research is relevant to engineering education for two reasons. Firstly, the emphasis ondeveloping strong mathematics skills during science teacher training is, in part, to ensuremathematically knowledgeable science teachers in schools, which is important to foster the nextgeneration of engineers. This is particularly relevant in Norway, whose economy relies heavily onthe petroleum industry. Secondly, the results from using KA in the physics course for scienceteachers (algebra based with a focus on conceptual understanding) are relevant to physics coursesfor engineering students.The motivation for this project was prior students' struggles with the mathematical aspect of theintroductory physics course for science teachers. In an attempt to remedy this, KA together withvoluntary mathematics tutorials were offered to one class of science teacher education students inthe introductory physics course in the fall semester of 2014 (N = 24). The course accounts forapproximately 25% of the students' semester work-load, and comprises eight three-hour classes,where the eighth class is reserved for group presentations for revision.All students created a KA account at the beginning of the semester, and were encouraged to use KAduring the semester for mathematics support. Students were given four relevant topics to completebefore each of the first seven classes. Completion referred to answering five questions correctly in arow on the topic. For those who struggled, hints and short videos explaining the topic wereavailable, as well as numerous problems to work on. The pre-work was voluntary, but if studentscompleted at least 21 of 28 topics, they were exempt from submitting the last of four questions inthe final physics assignment. Starting in the second week of class, fortnightly two-hour voluntarymathematics tutorials were offered to all students. The eight students with the lowest scores on amathematics pre-test were explicitly encouraged to attend. The mathematics test was developedspecifically for the purpose of this project, and contained 26 questions (all worth 2 marks) coveringboth familiar and unfamiliar topics. The average score on the pre-test was 21.6 (SD = 5.7; N = 22).The assessment methods used are individual data on students' use of Khan Academy, themathematics pre- and post-test, physics and mathematics tutorial class attendance, and a courseevaluation questionnaire containing some questions about the use of KA. By the time of abstractsubmission, the classes of the physics course had just concluded (total attendance at 95%), but thecourse evaluation and mathematics post-test had not been collected. Preliminary results, however,reveal that 22 of 24 students complied with the use of KA. Over the course of 9 weeks, they spenton average 12 hrs 22 mins (SD = 6 hrs 1 min; N = 22) on KA. They completed on average 22.3 (SD= 6.1; N = 22) out of 28 pre-work topics, and achieved the level of 'practiced' (evidence of basiccompetency shown) in an average of 148 topics (SD = 46; N = 22) out of a total of 905 topicscurrently in KA. When the mathematics post-test data is collected, students' learning gain will becorrelated with the variables collected from KA and mathematics tutorial attendance.Link to empirical data:https://www.dropbox.com/s/mm2tuuh4kchr9ev/Data%20for%20ASEE%20abstract.xlsx?dl=0
Lindstrøm, C. (2015, June), Using Khan Academy to support students' mathematical skill development in a physics course Paper presented at 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.25005
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