Frontline Learning Research (E-Journal - EARLI, European Association for Research on Learning)
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The Multidimensional Structure of Interest
Full text linkThere is increasing attention for interest as a powerful, complex, and integrative construct, ranging in appearance from entirely momentary states of interest to longer-term interest pursuits. Developmental models have shown how these situational interests can develop into individual interests over time. As such, these models have helped to integrate more or less separate research traditions and focus the attention of the field more on the developmental dynamics. This, however, also raises subsequent questions, one being how development can be understood in terms of interest structure. The developmental models seem to suggest that development occurs roughly along the line of six dimensions, which we summarize as the dimensions of historicity, value, agency, frequency, intensity, and mastery. Using an experience sampling method that was implemented in a smartphone application, we prompted 94 adolescents aged 13 to 16 (60% female) to rate each interest they experienced during two weeks on these six dimensions. A latent profile analysis on 1247 interests showed six distinct multidimensional patterns, indicating both a homogeneous and heterogeneous structure of interest. Four homogeneous patterns were indicated by more or less equal levels on all six dimensions in varying degrees, and contained 86% of the interests. Two heterogeneous patterns were found, describing variations of interest that are interpreted and discussed. These results endorse the complexity of the construct of interest and provide suggestions for identifying different manifestations of interest
Types of social help-seeking strategies in different and across specific task stages of a real, challenging long-term task and their role in academic achievement
Full text linkSocial help seeking (SHS) is an important strategy for successful self-regulated learning at all school levels. The aim of this longitudinal study is threefold: to ascertain the existence of different types of SHS strategies in various task stages of creating an individual academic paper, examine the extent to which these types of SHS strategies change in the course of that challenging long-term task and analyse the extent to which these types are relevant to academic achievement. This examination extends previous studies by adopting a task-specific, person-centred development perspective on SHS outside regular classroom instruction. In particular, we explore SHS types in the context of a real, long-term task, whereby aspects neglected in previous studies (need for help, help sources based on specific issue areas) are used for type creation and test for differences in academic achievement. Three online questionnaires were completed by 603 upper secondary school-level students (62.9% female) with a mean age of 17.3 (SD = .71) within one school year. Latent class analyses, latent transition analyses (LTA) and nonparametric procedures (Kruskal-Wallis H test, post hoc Dunn-Bonferroni test) were performed. Different SHS types were identified (independents, factual supervisor-focused, factual supervisor-focused and motivational family-focused, motivational family-focused, and factual and motivational family-focused) and found to vary over different task stages. Moreover, LTA indicated a considerable change between the SHS types over time. Nevertheless, no significant differences in achievement emerged between the types per task stage, thus reflecting the adage, 'There is more than one way of doing it'
Uncovering Patterns in Constructionist Collaborative Learning Activities via Cluster Analysis of Museum Exhibit Log Files
No full textA driving factor in designing interactive museum exhibits to support simultaneous users is that visitors learn from one another, via both observation and conversation. Such collaborative interactions among museum-goers are typically analyzed through manual coding of live- or video-recorded exhibit use. We sought to determine how log data from an interactive multi-user exhibit could indicate patterns in visitor interactions that could shed light on informal collaborative constructivist learning. We characterized patterns from log data generated by an interactive tangible tabletop exhibit using factors like "pace of activity" and the timing of “success events." Here we describe processes for parsing and visualizing log data and explore what these processes revealed about individual and group interactions with interactive museum exhibits. Using clustering techniques to categorize museum-goer behavior and heat maps to visualize patterns in the log data, we found that there were distinct trends in how users approached solving the exhibit: some players seemed more reflective while others seemed more achievement oriented. We also found that the most productive sessions occurred when all four areas of the table were occupied, suggesting that the activity design had a desired outcome to promote collaborative activity. 
Students’ observed engagement in lessons, instructional activities, and learning experiences
Full text linkIn order to expand previous intraindividual studies of student engagement we investigated students' observed engagement (i.e., on- and off-task behaviour), instructional activities (i.e., teacher-led whole class, individual work, pair-work, student-teacher interaction, assessment, and ”other”), and self-reported learning experiences (cognitive engagement, difficulty, competence, emotional engagement, positive and negative emotions), within lessons during one calendar week. Eighteen fourth and fifth grade target students (Mage=10.1, SD=0.44) were observed every 30 sec during two to four lessons each day for five school days (engagement and instructional activities), on average 66.05 times per lesson (SD=19.16, Range=15-80, nobs=14,994) between 9-18 lessons during a week. Simultaneously, students provided 1-3 electronic questionnaire self-reports per lesson (Mself_report=35.1, SD=12.6, Range=19-52, nself_report=631). We regressed observed engagement (0 = off-task, 1 = on-task) on self-reported learning experiences using 3-level (time-points nested in lessons, nested in students) Bayesian logistic regression models in brms. Observed engagement diminished during lessons, and was predicted by higher cognitive engagement, and instructional activities. As compared to teacher-led instruction, engagement was higher during individual tasks, teacher-supported tasks, and assessments. Overall self-reported and observed engagement within lessons converged, supporting their use in intraindividual research
The Happy Victimizer Pattern in Adulthood: State of the Art and Contrasting Approaches: Introduction to the Special Issue
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Opening the black box of students’ text-learning processes: A process mining perspective
Full text linkThe current study uncovers secondary school students’ actual use of text-learning strategies during an individual learning task by means of a concurrent self-reported thinking aloud procedure. Think-aloud data of 51 participants with different learner profiles, distinguished based on a retrospective self-report questionnaire (i.e., 15 integrated strategy users, 15 information organizers, 10 mental learners, and 11 limited strategy users), were analysed by means of educational process mining. Both the frequency of students’ strategy use, as well as the temporal patterns between these strategies were studied. The process mining results clearly demonstrated differences between students with different learner profiles with respect to the frequency of their applied strategies, as well as concerning the sequences wherein strategies were applied throughout the course of students’ text-learning process. The added value of combining both retrospective and concurrent self-report measures of students’ strategies as well as conducting process mining analysis is discussed
Self-Report is Indispensable to Assess Students’ Learning
Full text linkSelf-report is required to assess mental states in nuanced ways. By implication, self-report is indispensable to capture the psychological processes driving human learning, such as learners’ emotions, motivation, strategy use, and metacognition. As shown in the contributions to this special issue, self-report related to learning shows convergent and predictive validity, and there are ways to further strengthen its power. However, self-report is limited to assess conscious contents, lacks temporal resolution, and is subject to response sets and memory biases. As such, it needs to be complemented by alternative measures. Future research on self-report should consider not only closed-response quantitative measures but also alternative self-report methodologies, make use of within-person analysis, and investigate the impact of respondents’ emotions on processes and outcomes of self-report assessments.  
Regulating distance to the screen while engaging in difficult tasks
Full text linkRegulation of distance to the screen (i.e., head-to-screen distance, fluctuation of head-to-screen distance) has been proved to reflect the cognitive engagement of the reader. However, it is still not clear (a) whether regulation of distance to the screen can be a potential parameter to infer high cognitive load and (b) whether it can predict the upcoming answer accuracy. Configuring tablets or other learning devices in a way that distance to the screen can be analyzed by the learning software is in close reach. The software might use the measure as a person-specific indicator of need for extra scaffolding. In order to better gauge this potential, we analyzed eye-tracking data of children (N = 144, Mage = 13 years, SD = 3.2 years) engaging in multimedia learning, as distance to the screen is estimated as a by-product of eye tracking. Children were told to maintain a still seated posture while reading and answering questions at three difficulty levels (i.e., easy vs. medium vs. difficult). Results yielded that task difficulty influences how well the distance to the screen can be regulated, supporting that regulation of distance to the screen is a promising measure. Closer head-to-screen distance and larger fluctuation of head-to-screen distance can reflect that participants are engaging in a challenging task. Only large fluctuation of head-to-screen distance can predict the future incorrect answers. The link between distance to the screen and processing of cognitive task can obtrusively embody reader’s cognitive states during system usage, which can support adaptive learning and testing
A comparison of self-reports and electrodermal activity as indicators of mathematics state anxiety.: An application of the control-value theory
Full text linkIn the present study with 86 undergraduate students, we related trait Mathematics Anxiety (MA) with two indicators of state anxiety: self-reported state anxiety and electrodermal activity (EDA). Extending existing research, we included appraisals of control and perceived value in hierarchical multiple regression analyses in accordance with the control-value theory of achievement emotions (Pekrun, 2006). Results showed that trait MA predicted self-reported state anxiety, while no additional variance was explained by including control and value. In contrast, we found no significant relation between trait MA and physiological state anxiety, but a significant, negative three-way interaction effect with control and value. Regression coefficients indicated that trait MA predicted physiological state anxiety, but only in the presence of negative perceived control and positive perceived value. Thus, our results support the control-value theory for physiological state anxiety, but not for self-reports. They emphasize the need to distinguish between trait and state MA, the advantages of adopting the control-value theory, and the benefits of using EDA recording as a supplemental assessment method for state anxiety
Are Schools Alienating Digitally Engaged Students? Longitudinal Relations between Digital Engagement and School Engagement
Full text linkThis article examined digital learning engagement as the out-of-school learning component that reflects informally emerging socio-digital participation. The gap hypothesis proposes that students who prefer learning with digital technologies outside of school are less engaged in traditional school. This hypothesis was approached from the framework of connected learning, referring to the process of connecting self-regulated and interest-driven learning across formal and informal contexts. We tested this hypothesis with longitudinal data. It was of interest how digital engagement, operationalized as a general digital learning preference, wish for digital schoolwork, and their interaction, is related to traditional school engagement. This was examined both cross-sectionally in three time points and longitudinally across three years. The participants were 1,705 (43.7% female) 7th–9th graders (13-15 years old) from 27 schools in Helsinki, Finland. We explored the structure of correlations between latent constructs at each time point separately, and finally, to evaluate longitudinal relations between digital engagement and school engagement we specified latent cross-lagged panel models. The results indicate that students holding a stronger general digital learning preference experienced higher schoolwork engagement, both contemporaneously and over time, indicating successful connected learning. However, the results also showed support for the gap hypothesis: Students who preferred digital learning but did not have the chance to digitally engage at school, experienced a decrease in school engagement over time. The article shows that there is a need to examine the reciprocal interactive processes between the learners and their social ecologies inside and outside school more closely.