Frontline Learning Research (E-Journal - EARLI, European Association for Research on Learning)
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A dual pathway of student motivation: Combining an implicit and explicit measure of student motivation
Full text linkAbundant research in social psychology shows human behaviour is guided by beliefs through two pathways, a deliberate and automatic pathway. Research on student motivation has thus far focused mostly on the deliberate pathway and consequently almost exclusively relied on explicit measures (i.e. self-reports of motivation) to assess student motivation and subsequently predict student behaviour and achievement. The purpose of this study was to examine whether student motivation is associated with students’ behavioural engagement and school grades through dual pathways by assessing motivation with a newly developed implicit measure and an explicit measure. Participants were 139 students in year 3 of secondary education (58% female, M = 14.8 years). Motivation was assessed with an implicit association test (IAT) as well as an explicit measure (self-report). Behavioural engagement was assessed by teacher ratings, and school grades were reported by students. The explicit and implicit measures of student motivation were not significantly correlated, suggesting that both measures tap into different aspects of student motivation. Furthermore, structural equation analyses revealed that students’ explicit and implicit motivation were positively associated with school grades. Neither motivation measure was associated with teacher ratings of behavioural engagement. This study contributes to existing research by showing that an implicit measure of student motivation can predict unique variation in school grades in addition to an explicit measure. As such, the current study provides initial support for a dual pathway model of student motivation
Effects of progressive inquiry on cognitive and affective learning outcomes in adolescents’ geography education
Full text linkAdolescents need skills to acquire information and compare, analyze, transform, and experiment with knowledge. However, little research has been conducted on the content and pedagogical practices that are necessary to achieve these skills. This article seeks to contribute to this discussion because geography enables the attainment of the so-called higher-order thinking skills, and the progressive inquiry model provides suitable pedagogical practices. This study provides empirical evidence on the effects of the progressive inquiry teaching method and learning models on cognitive and affective learning outcomes. This paper focuses on learning outcomes among 253 Finnish middle and upper secondary school students. This comparison between different developmental stages reveals the effects of the teaching and learning methods in question. The results indicate that the progressive inquiry method improves cognitive learning results at both educational levels in the context of geography education. The research provides evidence that older students benefit more from the learning model. Additionally, the self-regulated learning skills that the students possess at the beginning of the course do not affect their cognitive learning outcomes. Progressive inquiry clearly enhances the motivation levels of middle school students; however, the effect on the motivation level was more ambiguous among the upper secondary students.
Testing a Unified Model of Task-specific Motivation: how teachers appraise three professional development activities
Full text linkThis article tests the tenability of a Unified Model of Task-specific Motivation (UMTM). The UMTM integrates task-specific components from several theories of motivation. Core of the model are four interacting but relatively independent types of valences. Affective and cognitive valences represent feelings while doing an activity and thoughts about the value of its consequences respectively; both affective and cognitive valences can be positive and negative, hence calling for approach and avoidance motivation respectively. The interaction between these four types of valences results in a valence appraisal that influences readiness for action. Task-specific antecedents, autonomy, feasibility, social relatedness and subjective norm, influence valences. 441 Primary school teachers provided judgments of all components of the model except social relatedness for three imaginary professional learning activities. The three activities were framed as a school board decided, a team decided and a personally decided learning activity. Structural equation modelling showed that for each activity a separate model was needed. How valences influenced readiness for action was specific to each activity. In the board and team decided activities, for instance, readiness for action appeared to be based predominantly on cognitive valences, while in the personally decided activity affective and cognitive valences showed a more balanced contribution. Regarding task-specific antecedents, however, the picture was less clear. Nevertheless, the UMTM proved to offer rich possibilities for the explanation of complex motivational phenomena and promises a significant reduction of the superabundance of theories that encumbers motivation research
It’s Not Only What You Say, But How You Say It: Investigating the Potential of Prosodic Analysis as a Method to Study Teacher’s Talk
Full text linkIn this study, we introduce new insights into prosodic analyses as an emerging method to study teacher talk. We claim that the prosodic aspects (features of speech such as intonation, volume, and pace) of talk are important, but under-represented in the learning sciences. These prosodic aspects may be used to complement, intensify or even reverse the linguistic content of speech. Thus far, most research on classrooms has focused on the content (what is said) rather than on understanding the meaning of the prosodic features (how it is said) of talk. In this study, we introduce prosodic analyses as a method to study classroom discussions. Our exploratory experiment focuses on the prosodic perspective of teacher’s talk to shed light on the features of classroom talk. We present a case in which we align prosodic features with the content of teacher's talk during a nine-week physics course. This article shows that prosodic analyses may have added value for research on learning and professional development. Namely, we illustrate that acting in an authentic classroom setting might trigger specific prosodic aspects in teacher's talk. We further found indications that the teacher applied different voice prosody regarding certain patterns of classroom talk. For the future, we suggest that a combination of content and prosodic analysis is a promising tool for gaining new insights into classroom talk
A Quantitative Exploration of Two Teachers with Contrasting Emotions: Intra-Individual Process Analyses of Physiology and Interpersonal Behavior
Full text linkAlthough the association between teacher-student relations, teacher emotions, and burnout has been proven on a general level, we do not know the exact processes underlying these associations. Recently there has been a call for intra-individual process measures that assess what happens from moment-to-moment in class in order to better understand inter-individual differences in emotions and burnout between teachers. This paper explored the use of process measures of teachers’ heart rate and their interpersonal behavior during teaching. Our aim was to illustrate different ways of analyzing and combining physiological and observational time-series data and to explore their potential for understanding between-teacher differences. In this illustration, we focused on two teachers who represented contrasting cases in terms of their self-reported teaching-related emotions (i.e., anxiety and relaxation) and burnout. We discuss both univariate process analyses (i.e., trend, autocorrelation, stability) as well as state-of-the-art multivariate process analyses (i.e., cross-correlations, dynamic structural equation modeling). Results illustrate how the two teachers differed in the nature of their physiological responses, their interpersonal behavior, and the association between these two process measures over time. Along implications and suggestions for further research, it is discussed how the process-based, dynamic assessment of physiology and interpersonal behavior may ultimately help to understand differences in more general teaching-related emotions and burnout
Field-Identification IAT predicts students’ academic persistence over and above Theory of Planned Behavior constructs
Full text linkAjzen and Dasgupta (2015) recently invited complementing Theory of Planned Behavior (TPB) measures with measures borrowed from implicit cognition research. In this study, we examined for the first time such combination, and we did so to predict academic persistence. Specifically, 169 first-year college students answered a TPB questionnaire and completed a field-identification Implicit Association Test (IAT). The IAT measure largely predicted academic persistence 6 months later over and above TPB constructs, including behavioral intention. We discuss interpretations of this finding and its relevance to educational research
A Deeper Understanding of Metacomprehension: Development of a New Multidimensional Tool
No full textThe purpose of this research endeavor was to develop and validate a new measurement tool predicated on previous research to assess learners’ metacomprehension during reading. In two separate studies (N = 923) with Chilean undergraduate students, we demonstrate the versatility and utility of our proposed Metacomprehension Inventory (MI). In Study 1, we provide empirical support for the psychometric soundness and construct validity of the MI. In Study 2, we provide evidence of the measurement invariance of the MI between males and females. Results of Study 1 revealed the hypothesized factor structure of the MI is sound, with high factor loadings, excellent model fit, and moderate-to-strong inter-factor correlations. Study 2 results indicated that the MI is interpreted similarly by both males and females, as factor loadings were largely statistically identical across the two groups. We discuss implications of our proposed MI for theory and applied research
Neuroimaging of learning and development: improving ecological validity
Full text linkModern neuroscience research, including neuroimaging techniques such as functional magnetic resonance imaging (fMRI), has provided valuable insights that advanced our understanding of brain development and learning processes significantly. However, there is a lively discussion about whether and how these insights can be meaningful to the educational practice. One of the main challenges is the low ecological validity of neuroimaging studies, making it hard to translate neuroimaging findings to real-life learning situations. Here, we describe four approaches that increase the ecological validity of neuroimaging experiments: using more naturalistic stimuli and tasks, moving the research to more naturalistic settings by using portable neuroimaging devices, combining tightly controlled lab-based neuroimaging measurements with real-life variables and follow-up field studies, and including stakeholders from the practice at all stages of the research. We illustrate these approaches with examples and explain how these directions of research optimize the benefits of neuroimaging techniques to study learning anddevelopment. This paper provides a frontline overview of methodological approaches that can be used for future neuroimaging studies to increase their ecological validity and thereby their relevance and applicability to the learning practice.
 
Towards a Methodological Framework for Sequence Analysis in the Field of Self-Regulated Learning
Full text linkIn recent decades, conceptualizations and operationalizations of self-regulated learning (SRL) have shifted from SRL as an aptitude to SRL as an event. Alongside this shift, increased technological capability has introduced computer log files to the investigation of SRL, uncovering new research avenues. One such avenue investigates the time-related characteristics of SRL through learners’ behavioural sequences. Although sequence analysis is still relatively new in SRL research, other fields have fruitful traditions in its application and may serve as a basis for applications in the field of SRL. Ten years of investigating SRL through sequence analysis have produced a wide range of methodological approaches. While this variety of methods illustrates the diversity of opportunities, it also indicates the lack of consensus regarding the most appropriate approach. Since the introduction of sequences analysis in the field of SRL, researchers have emphasized the need for a methodological framework to guide its application. Yet, to date, no such framework has been proposed, hindering our progress through (1) transparent methods and (2) comparative studies to (3) empirical and ecological applications. To help overcome this issue, this manuscript aims to foster discussions of a methodological framework for the use of sequence analysis in SRL research. We first make a case for why such a framework is necessary; secondly, we propose a set of considerations which could serve as a starting point for the construction of a framework
Do we betray errors beforehand? The use of eye tracking, automated face recognition and computer algorithms to analyse learning from errors
Full text linkPreventing humans from committing errors is a crucial aspect of man-machine interaction and systems of computer assistance. It is a basic implication that those systems need to recognise errors before they occur. This paper reports an exploratory study that utilises eye-tracking technology and automated face recognition in order to analyse test persons’ emotional reactions and cognitive load during a computer game and learning through trial and error. Computer algorithms based on machine learning and big data were tested that identify particular patterns of test persons’ gaze behaviour and facial expressions that antecede errors in a computer game. The results show that emotions and learning from errors are positively correlated and that gaze behaviour and facial expressions inform about the errors that follow. However, the algorithms still need to be improved through further studies to be suitable for daily use. This research is innovative in its use of mathematical formulae to operationalise learning through errors and the use of computer algorithms to predict errors in human behaviour in trial- and-error situations