### Using Khan Academy to support students' mathematical skill development in a physics course.

#### Christine Lindstrøm, Oslo and Akershus University College

*(The following is the abstract of a paper presented at the 2015 conference of American Society for Engineering Education**. The full paper can be found here. The research was supported by a MatRIC Small Research Grant, project number 140604).*

This paper (see link below) 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 their introductory physics course at a large teacher education institution in Norway.

By guiding the students 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 by working with a pedagogically well-designed mathematics learning tool. This research is relevant to engineering education for two reasons. Firstly, the emphasis on developing strong mathematics skills during science teacher training is, in part, to ensure mathematically knowledgeable science teachers in schools, which is important to foster the next generation of engineers. This is particularly relevant in Norway, whose economy relies heavily on the petroleum industry. Secondly, the results from using KA in the physics course for science teachers (algebra based with a focus on conceptual understanding) are relevant to physics courses for engineering students.

The motivation for this project was prior students' struggles with the mathematical aspect of the introductory physics course for science teachers. In an attempt to remedy this, KA together with voluntary mathematics tutorials were offered to one class of science teacher education students in the introductory physics course in the fall semester of 2014 (N = 24). The course accounts for approximately 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 KA during the semester for mathematics support. Students were given four relevant topics to complete before each of the first seven classes. Completion referred to answering five questions correctly in a row on the topic. For those who struggled, hints and short videos explaining the topic were available, as well as numerous problems to work on. The pre-work was voluntary, but if students completed at least 21 of 28 topics, they were exempt from submitting the last of four questions in the final physics assignment. Starting in the second week of class, fortnightly two-hour voluntary mathematics tutorials were offered to all students. The eight students with the lowest scores on a mathematics pre-test were explicitly encouraged to attend.

The mathematics test was developed specifically for the purpose of this project, and contained 26 questions (all worth 2 marks) covering both 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, the mathematics pre- and post-test, physics and mathematics tutorial class attendance, and a course evaluation questionnaire containing some questions about the use of KA. By the time of abstract submission, the classes of the physics course had just concluded (total attendance at 95%), but the course 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 spent on 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 basic competency shown) in an average of 148 topics (SD = 46; N = 22) out of a total of 905 topics currently in KA. When the mathematics post-test data is collected, students' learning gain will be correlated with the variables collected from KA and mathematics tutorial attendance.