The relation between task-specific motivational profiles and training of self-regulated learning skills

Need strength, perceived need support, stress symptomatology, and performance in the context of oral exams: A typological approach

Introduction

Based on self-determination theory, we investigated whether examinees are classifiable into profiles based on basic need strength and perceived need support that differ in stress parameters and achievement in the context of a standardized oral exam.

Methods

92 students reported their basic need strength before and perceived need support provided by the examiner once after the exam. Students indicated their emotions and stress perception at four measurement points and we measured their saliva cortisol concurrently, analyzing stress-related changes over time.

Results

Latent class analyses revealed two higher-quality (low/high, high/high) and two lower-quality (low/low, high/low) need strength/need support classes. Physio-affective stress development was typical of exam situations. Higher-quality classes that met or exceeded the needs displayed more beneficial stress and emotion response patterns than lower-quality classes. Gain-related emotions mediated achievement in the higher-quality classes.

Discussion

Need-supportive examiners can promote student well-being and achievement when they succeed in providing high need satisfaction.

Can active learning techniques simultaneously develop students' hard and soft skills? Evidence from an international relations class

PURPOSE

In recent decades, educators have pushed to implementing active learning techniques that can advance students' competences. Universities are increasingly required to develop knowledge measured in terms of grades (hard skills) and inter-personal, social, and communication abilities (soft skills). Nevertheless, within the field of active learning, educators often focus on how these techniques can improve students' hard skills and their satisfaction. Few have analysed whether and how these techniques might improve students' soft skills. Moreover, among these few studies, the majority has analysed hard and soft skills separately, measuring whether different active learning techniques may or may not improve them. Virtually no one has studied whether students' hard and soft skills can converge or diverge in an active learning format. This study allows us to understand the relations between these two sets of variables, for example, whether an improvement (or deterioration) in the hard skills corresponds to an improvement (or deterioration) in the soft skills, and vice versa.

METHOD

In our experiment, we analyse the impact of a specific active learning format, such as the Flipped Classroom (FC), on both students' hard and soft skills, by comparing it with a traditional class integrated with other active learning techniques, such as presentations, debates, and teamwork activities. First, we use Pearson correlations to measure the relation between students' hard skills, understood in terms of grades, and a set of soft skills, such as critical thinking, self-efficacy, teamwork, and perception of learning. Second, we use canonical correlations to analyse whether hard and soft skills converge or diverge in an FC format, in comparison with a traditional teaching format integrated with the other active learning techniques.

RESULTS AND CONCLUSIONS

Our main finding is that the FC per se neither improves nor worsens students' performance in terms of hard and soft skills.

Exploring Students’ Use of a Mobile Application to Support Their Self-Regulated Learning Processes

Being able to self-regulate one’s learning is essential for academic success but is also very difficult for students. Especially first year students can be overwhelmed with the high study load and autonomy in higher education. To face this challenge, students’ monitoring and self-regulated learning (SRL) processes are crucial. Yet, often students are not aware of effective SRL strategies or how to use them. In this study, the use of a mobile application with gamification elements (i.e., Ace Your Self-Study App) to support first-year university students’ SRL processes was investigated. In Study 1a, the Ace your self-study app was implemented in a first-year psychology course, and students’ SRL skills, motivation, self-efficacy, app use and satisfaction, and performance were measured. The results showed a significant increase in autonomous motivation, controlled motivation, and metacognitive self-regulation skills (MSR-R) across the 5-week course. Moreover, students who used the mobile application with gamified elements showed higher autonomous motivation. Nevertheless, most students used the app only for a limited number of self-study sessions. In Study 1b, students’ self-study experiences were captured using focus group interviews to shed some more light on why students did or did not use the app. The results show that if students feel they do not need support for their SRL processes during self-study, they are less inclined to use the app. Specifically, regarding using study strategies, it was found that only if students’ strategies do not work well in their perception, they feel the need to change their way of studying and choose another strategy. These results are discussed in the context of theory on SRL and how to support it.

Educational Neuroscience Training for Teachers' Technological Pedagogical Content Knowledge Construction

The attention to the laws of the brain and the mechanism of learning in the smart education era becomes the starting point for the convergence and development of education and neuroscience, which also inspired educational neuroscience (EN) affecting the teacher’s development. Although teachers always have a general curiosity about EN and its applications, the limited knowledge hinders their general practice, neuromyths begin to emerge, and there is no evidence to directly show the connection between EN and teachers’ technological pedagogical content knowledge (TPACK) knowledge. Based on an EN teacher training program for 216 teachers, this study verifies that EN training programs can promote teachers’ understanding of EN-related knowledge, and EN is also correlated to teachers’ TPACK. However, the EN training program does not promote high well-being and satisfaction. The research also analyzes the process of teachers’ EN knowledge dissemination based on interviews, and the research conclusion can further reveal the necessity of EN training for teachers in the future.

Predict or describe? How learning analytics dashboard design influences motivation and statistics anxiety in an online statistics course

Based on the achievement goal theory, this experimental study explored the influence of predictive and descriptive learning analytics dashboards on graduate students' motivation and statistics anxiety in an online graduate-level statistics course. Participants were randomly assigned into one of three groups: (a) predictive dashboard, (b) descriptive dashboard, or (c) control (i.e., no dashboard). Measures of motivation and statistical anxiety were collected in the beginning and the end of the semester via the Motivated Strategies for Learning Questionnaire and Statistical Anxiety Rating Scale. Individual semi-structured interviews were used to understand learners' perceptions of the course and whether the use of the dashboards influenced the meaning of their learning experiences. Results indicate that, compared to the control group, the predictive dashboard significantly reduced learners' interpretation anxiety and had an effect on intrinsic goal orientation that depended on learners' lower or higher initial levels of intrinsic goal orientation. In comparison to the control group, both predictive and descriptive dashboards reduced worth of anxiety (negative attitudes towards statistics) for learners who started the course with higher levels of worth anxiety. Thematic analysis revealed that learners who adopted a more performance-avoidance goal orientation approach demonstrated higher levels of anxiety regardless of the dashboard used.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11423-021-09998-z.

Development of a modular stress management platform (Performance Edge VR) and a pilot efficacy trial of a bio-feedback enhanced training module for controlled breathing

This paper describes the conceptual design of a virtual reality-based stress management training tool and evaluation of the initial prototype in a pilot efficacy study. Performance Edge virtual-reality (VR) was co-developed with the Australian Defence Force (ADF) to address the need for practical stress management training for ADF personnel. The VR application is biofeedback-enabled and contains key stress management techniques derived from acceptance and commitment and cognitive behavioural therapy in a modular framework. End-user-provided feedback on usability, design, and user experience was positive, and particularly complimentary of the respiratory biofeedback functionality. Training of controlled breathing delivered across 3 sessions increased participants' self-reported use of breath control in everyday life and progressively improved controlled breathing skills (objectively assessed as a reduction in breathing rate and variability). Thus the data show that a biofeedback-enabled controlled breathing protocol delivered through Performance Edge VR can produce both behaviour change and objective improvement in breathing metrics. These results confirm the validity of Performance Edge VR platform, and its Controlled Breathing module, as a novel approach to tailoring VR-based applications to train stress management skills in a workplace setting.

The Relation Between Students’ Effort and Monitoring Judgments During Learning: A Meta-analysis

Research has shown a bi-directional association between the (perceived) amount of invested effort to learn or retrieve information (e.g., time, mental effort) and metacognitive monitoring judgments. The direction of this association likely depends on how learners allocate their effort. In self-paced learning, effort allocation is usually data driven, where the ease of memorizing is used as a cue, resulting in a negative correlation between effort and monitoring judgments. Effort allocation is goal driven when it is strategically invested (e.g., based on the importance of items or time pressure) and likely results in a positive correlation. The current study used a meta-analytic approach to synthesize the results from several studies on the relationship between effort and monitoring judgments. The results showed that there was a negative association between effort and monitoring judgments (r = − .355). Furthermore, an exploration of possible moderators of this association between effort and monitoring was made. The negative association was no longer significant when goal-driven regulation was manipulated. Furthermore, it was found that the type of monitoring judgment (i.e., a weaker association for prospective judgments) and type of task (stronger association for problem-solving tasks relative to paired associates) moderated the relation between effort and monitoring. These results have important implications for future research on the use of effort as a cue for monitoring in self-regulated learning.

The Role of Mental Effort in Fostering Self-Regulated Learning with Problem-Solving Tasks

Problem-solving tasks form the backbone of STEM (science, technology, engineering, and mathematics) curricula. Yet, how to improve self-monitoring and self-regulation when learning to solve problems has received relatively little attention in the self-regulated learning literature (as compared with, for instance, learning lists of items or learning from expository texts). Here, we review research on fostering self-regulated learning of problem-solving tasks, in which mental effort plays an important role. First, we review research showing that having students engage in effortful, generative learning activities while learning to solve problems can provide them with cues that help them improve self-monitoring and self-regulation at an item level (i.e., determining whether or not a certain type of problem needs further study/practice). Second, we turn to self-monitoring and self-regulation at the task sequence level (i.e., determining what an appropriate next problem-solving task would be given the current level of understanding/performance). We review research showing that teaching students to regulate their learning process by taking into account not only their performance but also their invested mental effort on a prior task when selecting a new task improves self-regulated learning outcomes (i.e., performance on a knowledge test in the domain of the study). Important directions for future research on the role of mental effort in (improving) self-monitoring and self-regulation at the item and task selection levels are discussed after the respective sections.

The Effect of Metacognitive Knowledge on Mathematics Performance in Self-Regulated Learning Framework-Multiple Mediation of Self-Efficacy and Motivation

Metacognition, self-efficacy, and motivation are important components of interaction in self-regulated learning (SRL). However, the psychological mechanism underlying the association among them in mathematical learning remained ambiguous. The present study investigated whether the relationship between metacognitive knowledge (MK) and mathematics performance can be mediated by self-efficacy and motivation. The sample comprised 569 students (245 male, Mage = 16.39, SD = 0.63) of Grade 10 in China. The MK in mathematics questionnaire, the self-efficacy questionnaire, the academic motivation scale, Raven advanced progressive matrix, and mathematics tests were used for data collection. Our results suggested that the mathematics performance could be predicted by MK, self-efficacy and intrinsic motivation. Moreover, the association between MK and mathematics performance was mediated by self-efficacy and intrinsic motivation, as revealed by a multiple mediation analysis. Additionally, there were sex differences in MK, self-efficacy and intrinsic motivation. The findings highlight the psychological mechanism in the mathematics of Chinese students and will help teachers to improve students’ mathematical learning in SRL framework more effectively. Implications for education and further studies are discussed.