The data was collected in MotoR (Not motivated - How regulation of learning builds up students’ will to learn?) project funded by the Academy of Finland [348765] and carried out with the support of LeaF research infrastructure, University of Oulu. The site of the MotoR project is Learning and Educational Technology Research Lab (LET), University of Oulu (https://www.oulu.fi/let/). The MotoR multimodal process data set is collected to study secondary school students’ situational motivation and socially shared regulation of learning during a collaborative learning task. Research design and data sources The MotoR research design was structured around a multidisciplinary learning period that was part of the students’ biology and chemistry studies. The collaborative science task (described in detail later on) was completed at the University of Oulu in the LeaF research infrastructure (http://www.oulu.fi/leaf-eng), which is a classroom-like learning and research space. MotoR data set consists of video, electrodermal activity (EDA), questionnaire, repeated situational self-report, and interview data. Before the data collection, students answered a questionnaire about motivation and motivation regulation in relation to biology and chemistry studies. Viljaranta & Tuominen’s (2018) expectancy-value-cost questionnaire, and Wolters & Benzon’s (2013) motivation regulation strategies questionnaire were revised, resulting in 35 items on expectancies, task values, and costs, and 26 items on motivation regulation strategies. In addition, background information, such as name, age, gender, and class, was asked. While working on a collaborative task, the students filled out repeated situational self-reports five times: once at the beginning (1), three times during (2-4), and once at the end (5) of the task. The repeated situational self-report measured individual situational appraisals of the expectancy for success, task values, and costs in relation to the group assignment. The seven expectancy-value-cost statements were modified from the Finnish translations of the expectancy-value-cost instruments (Viljaranta & Tuominen, 2018; Tuominen, 2013) used in prior studies (Gaspard et al., 2015; 2017; Juntunen et al., 2022). In addition, individuals’ situational appraisal of actualized group-level motivation regulation during the group assignment was measured with one statement in the last four repeated situational self-reports (2-5). The statement of motivation regulation was developed based on the contextualized SAGA instrument (Volet, 2001). At the beginning and the end of the task, students’ appraisals of group assignments were measured with 24 revised items of the contextualized SAGA instrument (Volet, 2001). The students’ collaborative working was video recorded to observe their socially shared regulation of learning (SSRL). At the time, three groups were present in the learning and research space, each group in their own separate room. Each group's collaboration was videotaped with one camera, one group microphone located either in the ceiling or at the table, and with personal microphones. Altogether, the observational data included 38 hours of video, with the learning sessions’ mean duration being 90 minutes. Shimmer 3 GSR+ sensors (Realtime Technologies Ltd, Dublin, Ireland) were used to record students’ electrodermal activity with the sampling rate of 128hz. The data of each group member was synchronized with the video recording based on timestamps. First, the data was visually inspected and EDA recordings indicating a missing contact of the electrode were removed from the data set. The EDA data was further processed with the Ledalab toolbox (Benedek & Kaernbach, 2010). First, large artifacts were corrected manually using spline interpolation. Butterworth low pass filter with frequency 0.5 and order 5 was then used to remove small movement artifacts from the signal. Signal was decomposed into phasic and tonic components using Continuous Decomposition Analysis. Non-specific skin conductance responses with minimum amplitude of 0.01μS were detected from the signal (Dawson et al., 2017). Stimulated recall interviews were conducted directly after the completion of the collaborative science task. Each participant was interviewed individually. The interviews were video recorded, and one interview lasted from ten to twenty minutes. The interview included two parts. The first part included questions about the student’s general feelings about the group assignment. The second part considered motivation & regulation during the group assignment. First, students were asked to describe what they think motivation is and how it can be affected. Next, the interview moved on to the stimulus phase, in which the student was presented with visualizations derived from self-reported data filled out during the task. The interviewer asked reasons for students’ initial levels of expectancy for success, values, and costs as well as reasons for the changes in those motivational appraisals during the group assignment. The groups’ task performance was evaluated with an evaluation rubric, developed by the science teachers, throughout the task by the observing researcher. The rubric criteria were scored separately for each task phase. Additionally, in the stimulated recall interviews, the students were asked to grade their groups’ working on a scale from 1-10. Participants 95 8th-grade students from one upper secondary school in Oulu, Finland, participated in this study. The participants were between the ages of 13 and 16, with an average of 14,17 years (SD = .585), from which 40 students were female (42,11 %) and 51 students were male (53,68 %). One participant did not want to define their gender, and three participants did not document their gender. Additionally, five participants did not define their age. The students came from six classrooms, and they were divided into 31 small groups (five groups of two, 19 groups of three, and seven groups of four). Collaborative science task The students did a collaborative science task which was designed in collaboration with the school’s science teachers. The collaborative science task was a part of a bigger multidisciplinary learning period, including both biology and chemistry. The collaborative science task was also graded, and the grade counted as a part of the whole grade from the bigger multidisciplinary learning period. In the learning task, the students needed to purify water with everyday utensils, such as a plastic bottle, coffee filters, sand, and gravel. Further, the collaborative science task had different phases: air sparging (phase 1), precipitation (phase 2), observation (phase 3), and filtration (phase 4). During air sparging (phase 1), the students shook the water bottle with dirty water for 30 seconds after which they poured the dirty water into a beaker and then from one beaker to another ten times. During precipitation (phase 2), the students added potassium alum to the dirty water and mixed it continuously for five minutes. In the observation phase (phase 3), the students observed the mixture for twenty minutes writing down their observations every five minutes. During filtration (phase 4), the students built a water filter with everyday supplies, cleaned the filter by pouring one to two liters of clean water through the filter, and after that filtered the mixture of dirty water and potassium alum. No detailed instructions on how to perform the phases were given to the students. Instead, the students had learned the principles of purifying water at the school before the collaborative science task occurred, and every group member had studied to become an expert on one of the task phases. In case the students did not know how to proceed with the task, or one expert was missing, the students were provided with an advice card that guided them through that particular task phase. Also, the students continued examining the purified water at school in their biology class as a part of the multidisciplinary learning period after they completed the learning task during the data collection. References: Gaspard, H., Dicke, A., Flunger, B., Schreier, B., Häfner, I., Trautwein, U., et al. (2015). More value through greater differentiation: Gender differences in value beliefs about math. Journal of Educational Psychology, 107, 663–677. Gaspard, H., Häfner, I., Parrisius, C., Trautwein, U., & Nagengast, B. (2017). Assessing task values in five subjects during secondary school: Measurement structure and mean level differences across grade level, gender, and academic subject. Contemporary Educational Psychology, 48, 67-84. Juntunen, H., Tuominen, H., Viljaranta, J., Hirvonen, R., Toom, A., & Niemivirta, M. (2022). Feeling exhausted and isolated? The connections between university students’ remote teaching and learning experiences, motivation, and psychological well-being during the COVID-19 pandemic. Educational Psychology. doi: 10.1080/01443410.2022.2135686 Tuominen, H. (2013). Julkaisematon oppiainekohtaisten arvostusten mittarin käännös. Helsingin yliopisto. Viljaranta, J., & Tuominen, H. (2018). Oppiaineiden arvostukset: tärkeää, hyödyllistä, kiinnostavaa vai kuormittavaa [Task values: important, useful, interesting, or costly]. In K. Salmela-Aro (Ed.), Motivaatio ja oppiminen, pp. 101–122. Juva: PS-kustannus. Volet, S.E. (2001). Significance of cultural and motivational variables on students' appraisals of group work. In F. Salili, C.Y. Chiu, & Y.Y. Hong (Eds). Student Motivation: The Culture and Context of Learning (ch15) (pp. 309-334). New York: Plenum. Wolters, C. A., & Benzon, M. B. (2013). Assessing and predicting college students' use of strategies for the self-regulation of motivation. The Journal of Experimental Education, 81(2), 199–221. https://doi.org/10.1080/00220973.2012.699901

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