Language: Japanese

ISSN: 0913-4220

Abstract/Notes: Students who develop and apply their self-directed learning skills have advantages in school over those who do not (Betts & Knapp, 1981; Candy, 1991; Guglielmino, 1977; Schunk & Zimmerman, 2012). This is because self-directed learning (SDL) skills enable autonomous learning where students self-initiate, solve problems, develop new ideas, and monitor themselves with minimal external guidance (Knowles, 1976; Zimmerman, 2000). Despite the importance of these skills, research shows that few students consistently engage in SDL (Dent & Koenka, 2016; Zimmerman & Schunk, 2001). Because of SDL's multi-faceted and complex nature, it is difficult to discern why this is the case (Dent & Koenka, 2016; Zimmerman & Schunk, 2001). Multiple dynamic, interacting factors, including maturation, environmental supports, and historical events, likely contribute to students’ SDL development (Hoyle & Dent, 2017). As such, recent literature suggests that a relational dynamic systems (RDS) approach can help elucidate the dynamic, context-dependent patterns by which SDL skills unfold (Hoyle & Dent, 2017). According to RDS theories, development occurs within multi-level, interacting, relational systems; therefore, the bi-directional relationship between the person and their environment should be the unit of analysis (Lerner et al., 2011). This study aimed to provide a systematic investigation of the development of SDL skills, accounting for important contextual and developmental influences as well as individual pathways. Adolescence appears to be an optimal time for students to gain SDL skills (Brown, 1978; Brown et al., 1983); hence, this study focused on that developmental period. Also, because the Montessori educational approach is conducive to SDL skill development (Lillard, 2017; Rathunde, 2009, 2014), it was used as the school backdrop for this study. Furthermore, during data collection, a global pandemic caused by COVID-19 impacted school environments and was also included as a developmental context in this study. Specifically, this study utilized a longitudinal convergent mixed methods design to (1) identify patterns of SDL skill development across adolescence, (2) illustrate the reasons for those changes, and (3) illuminate the indirect effect of COVID-19 on students’ SDL. Emergent themes from student interviews conducted over four years augmented growth curve analysis results from an accelerated longitudinal design utilizing student surveys to address the research questions. Descriptive, correlational, multi-level model (MLM), and repeated-measures ANOVA analyses of student survey responses across four years (4 waves) of data collection with students grades 7 through 12 (n = 284) were applied to address the quantitative research questions. Emergent themes, derived through thematic analysis of 29 interviews, or 11 cases of students with a range of SDL skills (average, above average, and below average), addressed the qualitative research questions. Finally, quantitative results and qualitative findings were combined and compared to investigate convergence, divergence, and expansion areas that addressed integrative research questions. Findings shed important light on the development of adolescent students’ SDL skills across adolescence. Quantitative results and qualitative analyses were combined to address the research question: Do adolescent students’ SDL skills increase, decrease, or remain stable throughout middle school and high school? Findings resulted in areas of convergence and divergence across methods. Despite some diverging quantitative results, namely a non-significant growth model, other quantitative results, a non-significant no-growth model and descriptive plots, converged with qualitative findings from student interviews to suggest that within and between students, SDL skill development can include a combination of growth, decline, or stability over time. Findings from this study also suggest that each SDL skill can develop on its own timetable. Also, findings suggest a developmental pattern whereby SDL skills vary more in middle school than in high school. These findings have begun to disentangle contradictory results of earlier SDL research (e.g., Heater, 2005; Pajares & Valiante, 2002; Reio & Ward, 2005). From a practice perspective, the findings imply that it may benefit students to have tailored interventions that meet them where they are developmentally, considering each SDL skill individually and all together. The second integrative research question that was addressed in this study was: What roles do factors like grade level and the Montessori learning environment play in SDL development? Quantitative results and qualitative findings converged to suggest that students' SDL skills develop, at least in part, as a factor of the length of time a student has been immersed in the Montessori program. The findings also show that a student’s maturation may play a role in SDL skill development, especially when environmental contexts are supportive. In addition, qualitative interviews with students identified features of the Montessori program, such as open work time, scaffolded opportunities to be self-directed, autonomy support, and supportive teachers that aided students in their SDL development, which also aligns with the literature (Zumbrunn et al., 2011). This finding strengthens prior research, which found cursory evidence for how Montessori schools support the development of SDL skills (Ervin et al., 2010). In addition, quantitative results and qualitative findings diverged for the third overarching research question: Have changes in the learning environment associated with COVID-19 shaped the development of students’ SDL skills? If so, how? Although the quantitative results from this study failed to detect any indirect effects of the impact of COVID-19 on students’ SDL, qualitative findings found that changes in their learning environment as a result of COVID-19 impacted students’ SDL both negatively and positively. Research has also found that the global pandemic drastically impacted the school environment, so it is most likely that the quantitative measure failed to detect an effect (Huck & Zhang, 2021; Tarkar, 2020). Furthermore, in the interviews, most students reported a combination of negative experiences (e.g., more distractions at home, lowered motivation, fewer social interactions, higher stress, and missing in-school learning) as well as positive experiences (e.g., increased time management, access to resources, multi-tasking, organization, ability to shut out distractions, and time to sleep) that impacted their SDL abilities. Qualitative findings from this study extend prior research by providing student accounts of their experiences, including silver linings (Wilson et al., 2020). Despite its limitations, this study revealed important exploratory findings about how students’ SDL skills can develop across adolescence. Areas of convergence across qualitative and quantitative methodologies underscore the reliability of the study findings. There were also unique quantitative and qualitative findings that extend prior research and provide important implications for future research and practice.

Language: English

Published: Claremont, California, 2023

Abstract/Notes: A widely advocated idea in education is that people learn better when the flow of experience is under their control (i.e., learning is self-directed). However, the reasons why volitional control might result in superior acquisition and the limits to such advantages remain poorly understood. In this article, we review the issue from both a cognitive and computational perspective. On the cognitive side, self-directed learning allows individuals to focus effort on useful information they do not yet possess, can expose information that is inaccessible via passive observation, and may enhance the encoding and retention of materials. On the computational side, the development of efficient “active learning” algorithms that can select their own training data is an emerging research topic in machine learning. This review argues that recent advances in these related fields may offer a fresh theoretical perspective on how people gather information to support their own learning.

Language: English

DOI: 10.1177/1745691612454304

ISSN: 1745-6916, 1745-6924

Abstract/Notes: When emotions, thoughts, and actions align, this is referred to as “self-congruency”. Therefore, this study aimed to determine how temporal covariance of the heart and brain signals were related to self-congruency. Thirty-eight healthy adults underwent functional magnetic resonance imaging to obtain neural markers of variability, whereas heart rate variability (HRV) was measured using photoplethysmography. Participants were also asked to report their level of self-congruency with a graphic rating scale. A cross-covariance analysis (CCA) was performed to assess the temporal covariance of signals arising from both organs, which was then correlated with self-congruency scores. Overall, the CCA results revealed brain-to-heart-driven interplay in brain regions involved in the neurovisceral integration model (e.g., ventromedial prefrontal cortex) and in emotion regulation (e.g., anterior cingulate). However, higher self-congruency scores were related to heart-to-brain-driven interplay in brain regions involved in emotion regulation and empathy. Together, the present findings suggest that, while global brain-to-heart-driven interplay occurs on average, it is heart-to-brain-driven interplay that reflects higher self-congruency. Given the impact of heart-brain interplay and self-congruency on mental health, further investigations on each concept could be interesting in developing tools for early intervention.

Language: English

Published: Aug 30, 2023

Language: German

Published: Wien, Austria: Jugend & Volk, 2020

ISBN: 978-3-7100-4362-8 3-7100-4362-X

Language: German

Published: Innsbruck, Germany: Studien Verlag, 2009

Edition: 1st ed.

ISBN: 978-3-7065-4721-5 3-7065-4721-X

Series: Initiative neues Lernen

Abstract/Notes: The Montessori method was an educational model devised at the beginning of the 20th century by the Italian pedagogue, physician, psychologist, and psychiatrist María Montessori (1870-1952). She observed that her students activated their intelligence and developed their personality by carrying out manual activities. In recent years, one of the activities that she used, gamification, is currently booming in teaching. Games based in words or letters are often used in language learning, either in presential lessons or in mobile applications. In our teaching innovation group (GINDOC-UB/180), we proposed to adapt those word games using codes so that students could achieve a self-learning on the nomenclature of biomolecules, thus improving their knowledge in metabolism. These code-based games were proposed to Biochemistry students at the Chemistry degree of the Universitat de Barcelona. Games were posted on the Virtual Campus using Moodle. A code is part of a communicative system, and it is defined as a set of elements that allows a message to be decoded. In biochemistry, the best-known code is the genetic code that translates 3 nucleotides to an amino acid. The code allows the students to see that it is a degenerated code, and it was the first code-based game used. Nevertheless, only 20 amino acids are involved, and some letters are missing. Thus, we also used other codes such as numeric codes, Morse code, Braille system code, or codes from other alphabets (Japanese katakana or hiragana, Cyrillic alphabet, Arabic alphabet, or runic alphabet). In this work some examples of the games that can be proposed to the students are shown. Proposed games were highly valued by students and allowed a self-learning on the proposed biomolecules. Games based on the genetic code were easier and more enjoyable for the students to solve, and they provided them with additional biochemical knowledge of protein translation.

Language: English

DOI: 10.46328/ijonest.176

ISSN: 2642-4088

Language: English

ISSN: 0956-1382

Language: English

ISSN: 0140-0460

Abstract/Notes: This study aims to know: (1) the difference in students’ mathematical understanding (SMU) between Brain Based Learning (BBL) and Montessori learning; (2) the difference in students’ Self-Regulated Learning (SRL) between Brain Based Learning (BBL) and Montessori learning; and (3) the difference in SMU between BBL and Montessori learning in each category of SRL. This quasi-experimental research applies a quantitative approach with a posttest only control group design. The selection of research samples was carried out using purpose sampling. The results of this study are: (1) there is no difference in understanding of mathematics between students who are taught with the BBL model or with the Montessori method; (2) there are no differences in SRL between learning classes; (3) there is no significant difference in SRL between categories in BBL and Montessori classes.

Language: English

ISSN: 2964-7479