Frontline Learning Research (E-Journal - EARLI, European Association for Research on Learning)
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Individual interest and learning in secondary school STEM education
Full text linkInterest research offers different hypotheses about the association between interest and learning outcomes. The standard hypothesis proposes that interest predicts learning outcomes: people acquire new knowledge about a topic they find interesting. The affective by-product hypothesis assumes that learning predicts interest: by learning something, people develop an interest in this topic. Finally, the reciprocal hypothesis states that interest and learning covary. This longitudinal study aimed to test the predictive validity of these three hypotheses in the context of secondary school STEM education. The participants were 104 Finnish 7th grade students aged 12-14. Data were collected at three times during the school year through questionnaires and grade evaluations in mathematics and biology. A partial least squares (PLS) path modeling approach was used to determine the relationships between interest and course grades across the three measurement points: at the beginning of the autumn semester, at the beginning of the spring semester, and after the spring semester at the end of the school year. The results differed between the autumn and spring semesters: During the autumn semester, students’ interest predicted their grades, whereas during the spring semester, grades predicted their interest. These findings indicate that the relationships between students’ individual interest towards science and mathematics with learning vary. As a practical implication, more focus should be put on when and what type of performance feedback is given to students with differing interest profiles.  
Experience and Meaning in Small-Group Contexts: Fusing Observational and Self-Report Data to Capture Self and Other Dynamics
Full text linkSelf-report data have contributed to a rich understanding of learning and motivation; yet, self-report measures present challenges to researchers studying students’ experiences in small-group contexts. Rather than using self-report data alone, we argue that fusing self-report and observational data can yield a broader understanding of students’ small-group dynamics. We provide evidence for this assertion by presenting mixed-methods findings in three sections: (a) self-report data alone, (b) observational data alone, and (c) the fusion of both data sources. We rely on 101 students’ self-reported experiences as well as observational (i.e., audio) data of students working in their group (N = 24 groups). In section order, we found that (1) students’ self-reported small-group behavior predicted their end-of-study reported anxiety and emotion; (2) coded observational data captured five types of group dynamics that students can engage in; and (3) students’ initial group-level characteristics predicted their real-time group dynamics, and observed group regulation activity predicted students’ self-reported anxiety, emotion, and regulation moving forward. Thus, while self-report and observational data alone can each increase our understanding of student motivation and learning processes, pursuing both in tandem more effectively captures the give-and-take among students, how these experiences evolve over time, and the personal meanings they can afford
The How of Survey Self-report: VAS-Likert-Slide-Swipe... Same difference?
No full textSelf-report is a fundamental research tool for the social sciences. Despite quantitative surveys being the workhorses of the self-report stable, few researchers question their format—often blindly using some form of Labelled Categorical Scale (Likert-type). This study presents a brief review of the current literature examining the efficacy of survey formats, addressing longstanding paper-based concerns and more recent issues raised by computer- and mobile-based surveys. An experiment comparing four survey formats on touch-based devices was conducted. Differences in means, predictive validity, time to complete and centrality were compared. A range of preliminary findings emphasise the similarities and striking differences between these self-report formats. Key conclusions include: A) that the two continuous interfaces (Slide & Swipe) yielded the most robust data for predictive modelling; B) that future research with touch self-report interfaces can set aside the VAS format; C) that researchers seeking to improve on Likert-type formats need to focus on user interfaces that are quick/simple to use. Implications and future directions for research in this area are discussed
Combining physiological data and subjective measurements to investigate cognitive load during complex learning
Full text linkCognitive load theory is one of the most influential theoretical explanations of cognitive processing during learning. Despite its success, attempts to assess cognitive load during learning have proven difficult. Therefore, in the current study, students’ self-reported cognitive load after the problem- solving process has been combined with measures of physiological data, namely, electrodermal activity (EDA) and skin temperature (ST) during the problem-solving process. Data was collected from 15 students during a high and low complex task about learning and teaching geometry. This study first investigated the differences between subjective and physiological data during the problem- solving process of a high and low complex task. Additionally, correlations between subjective and physiological data were examined. Finally, learning behavior that is retrieved from log-data, was related with EDA. Results reveal that the manipulation of task complexity was not reflected by physiological data. Nevertheless, when investigating individual differences, EDA seems to be related to mental effort
The effect of formal team meetings on teachers’ informal data use interactions
Full text linkIn recent years, the emphasis on interaction in data use has grown because of its potential to support individual teachers. However, in practice, teachers do not appear to interact widely in their use of data, either formally or informally. To gain knowledge of how sustainable data use interactions can be facilitated, this study investigated how formal data use in teams of teachers affects the teachers’ informal interactive data use. Social network analysis revealed that teachers with positive perceptions about formal data use become more active in their informal data use network, particularly within the problem diagnosis phase. Therefore, it is necessary to ensure strong connections between teachers in formal groupings in order to have an impact on their informal interactive behaviour
Processing and learning from multiple sources: A comparative case study of students with dyslexia working in a multiple source multimedia context
Full text linkThis study investigated how four 10th-grade students with dyslexia processed and integrated information across web pages and representations when learning in a multiple source multimedia context. Eye movement data showed that participants’ processing of the materials varied with respect to their initial exploration of the web pages, their overall processing time, and the linearity of their processing patterns, with post-learning interviews indicating the deliberate, strategic considerations underlying each participant’s processing pattern. Eye movement data in terms of fixation duration and percentage of regressions also corroborated the findings of formal, diagnostic assessments. Finally, it was found that participants differed with respect to how much factual information they learned from working with the materials and how well they were able to integrate information across the web pages and representations, with results suggesting particular problems with learning factual information and, at the same time, constructing a coherent mental representation of the issue, as well as with drawing on textual information in the integration process. This study brings together two research areas that essentially have been kept apart in theory and research, that is, dyslexia and multimedia learning, and it provides unique information about the role of individual differences in multiple source multimedia contexts
Measuring academic learning and exam self-efficacy at admission to university and its relation to first-year attrition: an IRT-based multi-program validity study
Full text linkSelf-efficacy is associated with both academic performance and attrition in higher education. Whether it is possible to measure students’ academic self-efficacy after admission and prior to commencing higher education (i.e. pre-academic self-efficacy) in a valid and reliable way has hardly been studied. Aims: 1) to evaluate the construct validity and psychometric properties of two short scales to measure Pre-Academic Learning Self-Efficacy (PAL-SE) and Pre-Academic Exam Self-Efficacy (PAE-SE) using Rasch measurement models, 2) to investigate whether pre-academic self-efficacy was associated with half-year attrition across degree programs and institutions. Data consisted of 2686 Danish students admitted to nine different university degree programs across two institutions. Item analyses showed both scales to be essentially objective and construct valid, however, all items from the PAE-SE and two from the PAL-SE were locally dependent. Differential item functioning was found for the PAL-SE relative to degree programs. Reliability of the PAE-SE was .77, and varied for the PAL-SE from .79 to .86 across degree programs. Targeting was good only for the PAL-SE, thus we proceeded with the PAL-SE. PAL-SE was found to be associated with half-year attrition: A difference in PAL-SE from minimum to maximum was associated with a difference in half-year attrition of approximately 7%. This association was found both in the bivariate model and in the multivariate models with control of degree program, and with control of degree program and individual covariates such as earlier educational achievement and social background variables. Results thus also indicate that PAL-SE has a causal effect on half-year attrition
Effectiveness of Self-Generation During Learning is Dependent on Individual Differences in Need for Cognition.
Full text linkSelf-generated information is better recognized and recalled than read information. This so-called generation effecthas been replicated several times for different types of stimulus material, different generation tasks, and retention intervals. The present study investigated the impact of individual differences in learners’ disposition to engage in effortful cognitive activities (need for cognition, NFC) on the effectiveness of self-generation during learning. Learners low in NFC usually avoid getting engaged in cognitively demanding activities. However, if these learners are explicitly instructed to use elaborate learning strategies such as self-generation, they should benefit more from such strategies than learners high in NFC, because self-generation stimulates cognitive processes that learners low in NFC usually tend not to engage in spontaneously. Using a classical word-generation paradigm, we not only replicated the generation effect in free and cued recall but showed that the magnitude of the generation effect increased with decreasing NFC in cued recall. Results are consistent with our assumption that learners higher in NFC engage in elaborate processing even without explicit instruction, whereas learners lower in NFC usually avoid cognitively demanding activities. These learners need cognitively demanding tasks that require them to switch from shallow to elaborate processing to improve learning. We conclude that self-generation is beneficial regardless of the NFC level, but our study extends the existing literature on the generation effect and on NFC by showing that self-generation can be particularly useful for balancing the learning disadvantage of students lower in NFC
Paradigmatic Issues in State-of-the-Art Research Using Process Data
Full text linkLearning science is enthusiastically adopting new instruments to gather physiological and other forms of event data to represent mental states and series of them that reflect processes. In an attempt to provoke more thought about this kind of research, I suggest paradigmatic issues relating to data, analyses of them and interpretations of results. I advocate we not label these data as “objective.” Instead, we share a subjective interpretation of them. I argue propositions about validity need more nuance. Bounds on generalization related to so-called ecological validity are rarely empirically justified. When researchers transform raw data before analysis and when analytic methods partition variance, interpretations of results omit key qualifications. I posit emotion and motivation be positioned in theory as moderators rather than mediators because agentic, self-regulating learners make and revise knowledge by choosing forms of cognitive engagement in a context where they interpret arousal. I note that researchers’ anchor interpretations of process data in learners’ accounts. This creates a tautology that troubles usual notions of reliability. Finally, I recommend research involving process data turn more toward helping learners identify conditions of learning that spark arousal so learners can regulate motivation and emotion. This leads to a surprise: Treating learners as individuals and helping them identify triggers of arousal may recommend learning science cast emotions and motivation as epiphenomena
Epistemic Beliefs and Googling
Full text linkWith the introduction of internet as a source of information, parents have observed youngsters’ tendency to prefer internet as a source, and almost a reluctance to learn in advance since “you can look it up when needed”. Questions arise, such as ‘Are these phenomena symptoms of changing beliefs about knowledge and learning? Is it at all possible to learn on a deeper level simply by looking up the basic facts, without memorizing them?’Within an existing line of investigation, epistemic beliefs have been described as a set of dimensions. Although internet-based information and internet as a source of information have been acknowledged, studies so far have not explored how dealing with internet-based information relates to other epistemic beliefs dimensions.To capture how users view internet-based information per se but also in relation to other epistemic beliefs, I suggest three new dimensions, out of which the most crucial is labelled ‘Internet reliance’. Offloading memory using memory aids is not a new phenomenon but the ‘Internet reliance’ dimension indicates that especially internet-reliant users may be confusing external information with personal knowledge, with all the risks it may entail.Besides including beliefs about learning, this study also challenges earlier assumptions regarding uncorrelated dimensions