This exploratory case study aimed to investigate patterns in student reasoning in statistical mechanics, in order to identify difficulties and develop ideas for future research. Upper-division undergraduate students, taking a course in statistical mechanics, were interviewed in groups. Here we present our findings regarding student difficulties in distinguishing microstates and macrostates, as well as distinguishable versus indistinguishable particles. We also present observed patterns of student reasoning about a simple, discrete system in contact with a heat bath. Our findings reveal problematic student intuitions of the high temperature limit. Several students were, however, able to transfer knowledge from a similar problem involving spin to improve their reasoning. / Denna explorativa fallstudie ämnade att undersöka mönster i studenters resonemang i statistisk mekanik, för att identifiera svårigheter och utveckla idéer för framtida forskning. Studenter i sista året på kandidatprogrammet i fysik, som läste en kurs i statistisk mekanik, intervjuades i grupper. Här presenterar vi våra fynd gällande studenters svårigheter med att skilja på mikrotillstånd och makrotillstånd, såväl som urskiljbara och ourskiljbara partiklar. Vi presenterar också observerade mönster i studenters resonemang kring ett simpelt, diskret system i kontakt med en värmereservoar. Våra fynd avslöjar problematiska intuitioner för gränsvärdet vid hög temperatur. Flera studenter kunde dock överföra kunskap från ett liknande problem, som handlade om spin, för att förbättra deras resonemang.

<p>Cognitive load theory (CLT) lays out a tripartite scheme concerned with how learners cognitively interact with instructional materials during learning and problem solving. Cognitive load refers to the utilization of working memory resources, and CLT designates three types of cognitive load as intrinsic cognitive load, extraneous cognitive load, and germane cognitive load. Intrinsic cognitive load is related to the intrinsic complexity of the material. Extraneous cognitive load is concerned with unnecessary utilization of cognitive resources due to suboptimal instructional design. Germane cognitive load results from processing the intrinsic load and schema acquisition. The expertise reversal effect follows as a consequence of CLT.  </p> <p>The expertise reversal effect (ERE) states that instructional materials that are beneficial to low prior knowledge (LPK) learners may be detrimental to high prior knowledge (HPK) learners. Less guided materials have been shown to reduce extraneous cognitive load for these learners and therefore produce a greater benefit.  </p> <p>In this work we present the development of online instructional modules that deliver content in two distinct styles, differentiated by their use of guiding features. the high level guidance version (HLG) uses guiding features, such as animations and voice narration, which have been shown to benefit LPK learners. Alternatively, guiding features have been shown to be destructive to the learning of HPK students. The low level guidance (LLG) version uses text in place of voice narration and pop-up content in place of continuous animations. Both versions led to a statistically significant improvement from pre-test to post-test. However, both HPK and LPK students showed a preference for the HLG version of the module, contrary to the ERE. Future work will focus on improving the ability to indentify HPK and LPK students, and refining methods for providing optimal instructional materials for these cohorts.  </p> <p>Meanwhile, the use of machine learning is an emerging trend in education. Machine learning has been used in roles such as automatic scoring of essays in scientific argumentation tasks and providing feedback to students in real time. In this work we report our results on two projects using machine learning in education. In one project we used machine learning to predict students’ correctness on a physics problem given an essay outlining their approach to solving the problem. Our overall accuracy in predicting problem correctness given a student’s strategy essay was 80%. We were able to detect students whose approach would lead to an incorrect solution at a rate of 87%. However, deploying this model to provide real-time feedback would necessitate performance improvement. Planned future work on this problem includes hand grading essays to produce a label that reflects the scientific merit of each essay, using more sophisticated models (like Google’s B.E.R.T.), and generalizing to a larger set of problems. </p> <p>In another study, we used data about students’ prior academic behavior to predict academic risk in a first-year algebra based physics course. Their final course grade was used to define their risk category as; B- and above is designated low risk, and C+ and below is designated as high-risk. Using a mix of numerical and category features such as high school gpa, ACT/SAT scores, gender, and ethnicity we were able to predict student academic risk with 75% overall accuracy. Students with a very high grade (A) or students with a very low grade (D,F,W) were identified at a rate 92% and 88% (respectively).</p> <p>Prior work has shown that performance can be greatly increased by including in-class features into the model. Future work will focus on obtaining raw data, rather than using curved scores reported to the university registrar. Also, obtaining more batches of data to improve predictive power with existing models developed in this study.<br> </p>

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<p dir="ltr">The study investigates the effectiveness of productive failure learning using a contrasting-cases design of ill-structured problems followed by well-structured problems. Fifty-one future elementary school teachers, enrolled in an undergraduate physics course were randomly assigned to one of the three conditions: a) ill-structured followed by well-structured problems (IS-WS), b) well-structured followed by well-structured problems (WS-WS), and c) ill-structured followed by ill-structured problems (IS-IS). The study hypothesized that the first condition with a contrasting-case design would outperform the non-contrasting-case design. After solving treatment problems in their respective conditions, all the participants took a post-test that comprised both ill-structured and well-structured problems. The one-way and two-way ANOVA results showed that while productive failure learning (IS-WS) outperformed WS-WS on both procedural and conceptual knowledge in the well-structured post-test, there was no significant difference between the three learning conditions in the ill-structured post-test. The findings indicated that structuring instruction lies on a continuum between highly structured and unstructured. For higher-level physics education, productive failure learning provided the optimum balance of discovery learning via ill-structured problems and guided instruction via well-structured problems to activate prior knowledge, draw attention to critical features of the canonical concept, and facilitate motivation and excitement within learners, resulting in effective learning.</p>

This thesis presents an investigation of undergraduate student learning with respect to physics lectures attended in English and Swedish. The work studies three connected areas: student learning patterns, bilingual scientific literacy and disciplinary discourse. Twenty-two physics students at two Swedish universities attended lectures in both English and Swedish as part of their regular undergraduate programme. These lectures were video-taped and used to contextualize in-depth, semi-structured interviews with students. When taught in English the students asked and answered fewer questions and reported be-ing less able to simultaneously follow the lecture and take notes. Students adapted to being taught in English by; asking questions after the lecture, no longer taking notes in class, read-ing sections of work before class or—in the worst case—by using the lecture for mechanical note taking. Analysis of student oral descriptions of the lecture content in both languages identified a small number of students who found it almost impossible to speak about disciplinary concepts in English. These students were first-years who had not been taught in English before. How-ever, the findings suggest that, above a certain threshold level of disciplinary language com-petence, it does not appear to matter which language students are taught in. Finally, the thesis makes a theoretical contribution to educational research. The initial lan-guage perspective is broadened to include a wide range of semiotic resources that are used in the teaching of undergraduate physics. Student learning is then characterized in terms of becoming fluent in a disciplinary discourse. It is posited that in order to achieve an appropri-ate, holistic experience of any given disciplinary concept, students will need to become fluent in a critical constellation of disciplinary semiotic resources.

This thesis examines meaning-making in three different areas of undergraduate physics: the refraction of light; electric circuits; and, electric potential and electric potential energy. In order to do this, a social semiotic perspective was constituted for the thesis to facilitate the analysis of meaning-making in terms of the semiotic resources that are typically used in the teaching and learning of physics. These semiotic resources include, for example, spoken and written language, diagrams, graphs, mathematical equations, gestures, simulations, laboratory equipment and working practices. The empirical context of the thesis is introductory undergraduate physics where interactive engagement was part of the educational setting. This setting presents a rich data source, which is made up of video- and audio recordings and field notes for examining how semiotic resources affect physics teaching and learning. Theory building is an integral part of the analysis in the thesis, which led to the constitution of a new analytical tool – patterns of disciplinary-relevant aspects. Part of this process then resulted in the development of a new construct, disciplinary affordance, which for a discipline such as physics, refers to the inherent potential of a semiotic resource to provide access to disciplinary knowledge. These two aspects, in turn, led to an exploration of new empirical and theoretical links to the Variation Theory of Learning. The implications of this work for the teaching and learning of physics means that new focus is brought to the physics content (object of learning), the semiotic resources that are used to deal with that content, and how the semiotic resources are used to create patterns of variation within and across the disciplinary-relevant aspects. As such, the thesis provides physics teachers with new and powerful ways to analyze the semiotic resources that get used in efforts to optimize the teaching and learning of physics.

The main purpose of this diploma thesis is to obtain information on how Matfyz can improve its cooperation with high school students and their physics teachers to increase students' interest in physics. To obtain these information a questionnaire was sent to physics teachers, who had been mentioned by Matfyz students as teachers who had had a positive effect on them. The questionnaire itself consists of four parts - events for students, events for physics teachers, Mat- fyz activities, and teaching. The data was processed using both quantitative and qualitative methods, whereas larger part of research was build on quantitative methods. The collected data showed that according to respondents the most im- portant task is to focus on non-Prague students. Thus, organizers should organize events in various places in the Czech Republic or use modern technologies and organize events on-line (that also applies to events for physics teachers). High school students might also meet with scientists and university physics students, visit laboratories except for visitors' days (e. g. during excursions, internships) or have an opportunity to find out how physics in companies is used. Respondents expressed support for writing a new physics textbook on Matfyz, one containing more difficult parts for talented students.

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