Self-motivated and directed learning across the lifespan

Enhancing pharmaceutical calculation proficiency: Exploring self-directed learning and self-reinforcement assessment strategies for student success

INTRODUCTION

Proficiency in pharmaceutical calculations is essential for pharmacy students, particularly for their role in patient care. This study is to explore the impact of self-directed learning (SDL) and self-reinforcement assessment (SRA), (SDL/SRA), strategies on student performance in pharmaceutical calculations at [COP name].

METHODS

The study was conducted from 2020 to 2022, which included first-year pharmacy students. The calculation curriculum comprised a pre-pharmacy refresher, a primer program, a comprehensive course, and an online SDL program. SDL/SRA methodologies were introduced in 2021 and 2022 to enhance student engagement and learning outcomes. Data was collected through course evaluations, anonymous surveys, and comparative performance analysis.

RESULTS

The implementation of SDL/SRA in 2021 and 2022 led to a notable improvement in student grades, with an increase of 13-17 % compared to 2020. Additionally, the failure rates dropped significantly from 30 % in 2020 to 2 % and 12 % in 2021 and 2022, respectively. Student feedback reflected a higher level of engagement and satisfaction with the course structure and the resources provided. Additionally, the analysis also identified challenges, particularly in understanding complex calculations and applying formulas to real-world scenarios.

CONCLUSION

SDL/SRA strategies have the potential to effectively enhance student performance and engagement in pharmaceutical calculations. However, the study's limitations, such as being conducted at a single COP, the absence of demographic data, variations in teaching formats between online and onsite, and reliance on student feedback rather than direct analytics, highlight the need for further research to validate these findings across diverse educational contexts.

Systematic Curiosity as an Integrative Tool for Human Flourishing: A Conceptual Review and Framework

This paper reviews seventy years of theoretical research and proposes systematic curiosity as an integrative tool for human flourishing with a focus on four key aspects: firstly, acknowledge curiosity's multidimensional nature instead of harmonizing its complex taxonomy; secondly, emphasizing intentional curiosity as opposed to impulsive curiosity; thirdly, prioritizing domain-general curiosity for broader applicability across educational, organizational, and therapeutic settings; and lastly, focusing on curiosity as a developable skill rather than an innate trait. By segmenting systematic curiosity into cognitive, emotional, and behavioral components, and relating these to interactions with the self, others, and the world, the framework aims to apply across the spectrum of human experience. Furthermore, the framework encourages an exploration of various evidence-based activities for flourishing so individuals can discover the most suitable strategies for their specific context. Implications for both theory and practice are examined, limitations are discussed, and avenues for future research are suggested.

Validation and adaptation of the moral outrage scale in the Peruvian adult population

BACKGROUND

Moral outrage (MO) is an emotional experience that arises in situations where a moral standard is violated. Despite its relevance, there are few psychometric studies in the Latin American context, characterized by inequality and social problems. This highlights the need for specific assessment instruments for this construct. The purpose of this study was to analyze the psychometric properties of an MO scale in the Peruvian population.

METHODS

The sample consisted of 881 Peruvians (57.2% women, Mage = 24.5 years, SD = 9.07 years). The moral outrage scale was administered to participants. To analyze the data, two models were tested: a structural equation model (SEM) and an exploratory structural equation model (ESEM).

RESULTS

The CFA confirmed a two-factor model (emotional and cognitive), with satisfactory fit indices and standardized factor loadings greater than 0.70. The ESEM model also showed improved fit indices. Measurement invariance across sex was established, and convergent validity was demonstrated between the dimensions of MO and authoritarianism, as well as other sociodemographic variables such as sex, age, and socioeconomic level.

CONCLUSIONS

The MO scale tested in this study is a reliable, valid, and invariant instrument, suitable for assessing moral outrage in both men and women within the Peruvian context.

The effectiveness of immersive virtual reality applications (human anatomy) on self-directed learning competencies among undergraduate nursing students: A cross-sectional study

Technological developments have significantly impacted various aspects of life, most notably healthcare and education. A nursing education shift was required to prepare digital generation. Consequently, nurse educators must adopt innovative approaches to teaching and learning, like incorporating immersive virtual reality (VR) into human anatomy courses to improve students' learning. To examine the influence of immersive VR applications (human anatomy) on self-directed learning (SDL) competencies among undergraduate nursing students. A cross-sectional design was conducted in the health profession's faculty at Al-Quds University among the first year of the nursing program, who were enrolled in an anatomy course (N = 137). The Self-Directed Learning Instrument was used, and independent sample t-tests were conducted to compare the level of SDL among students who utilized the VR application (Human Anatomy VR). The results showed that 93.9% of the total were approximately 20 years old, and 85.4% were females. 90.5% of participants expressed satisfaction with using the VR application and that it would be beneficial in nursing courses. The average score of SDL for the whole group was 72.03 ± 13.07, and there is a positive significant relationship between SDL and students utilizing VR (p < 0.001), between SDL competencies and technological skills (p = 0.009), and type of digital tools (p = 0.049). The highest coefficient of correlation was related to planning and self-monitoring (r = 0.918), and the lowest was related to interpersonal communications (r = 0.865). VR is an additional tool for enhancing learning, and nursing students perceive immersive VR technologies positively and prefer using three-dimensional images in their anatomy courses. SDL assists students in identifying learning objectives, barriers, and outcomes through using VR technologies as teaching strategies.

Self-directed learning in dental hygiene students: Impact of locus of control and personality traits

OBJECTIVES

The purpose of this study was to identify demographic variables, the level of self-directed learning (SDL), locus of control (LOC), and personality traits in dental hygiene (DH) students and to identify predictive variables for SDL.

METHODS

Cross-sectional survey research was conducted with a convenience sample of DH students (n = 229) in the United States using a web-based survey. The validated instruments used were the Self-Directed Learning Instrument (SDLI) to determine level of SDL, the Academic Locus of Control (ALC) scale for college students to evaluate LOC, and the Big Five Inventory-2-Extra Short Form (BFI-2-XS) to identify personality traits. Descriptive, correlation, and regression analyses were performed.

RESULTS

The completion rate was 68.9% (n = 159). The average SDLI score of the sample was 82.59, indicating a high overall level of SDL. The average ALC score was 10.34, indicating an overall internal LOC. Internal LOC (B = -0.319, SE = 0.082, β = -0.330, p < 0.001) and an open-minded personality trait (B = 1.156, SE = 0.363, β = 0.233, p = 0.002) emerged as significant predictors of learning motivation (B = -0.138, SE = 0.057, β = -0.214, p < 0.017) and self-monitoring (B = 0.553, SE = 0.253, β = 0.167, p = 0.030) SDLI constructs.

CONCLUSION

SDL among DH students can be cultivated by enhancing their learning motivation and self-monitoring skills. This may be achieved by helping learners increase their internal locus of control and open-mindedness. Future studies should explore exercises to help promote these traits.

Factors affecting children's direct learning and productive memory processes in the context of virtual museums

Informal educational opportunities such as visits to museums, aquariums, and zoos support children's semantic knowledge gain. Most research focuses on outcomes of direct learning, such as factual recall. The extent to which children engage in productive memory processes such as inferential reasoning and self-derivation through memory integration is not yet well understood. We assessed 8- to 9-year-old children's performance on tests of direct (e.g., fact recall) and productive (e.g., inference, integration) learning from virtual museum exhibits. We also examined the influence of children's involvement on learning outcomes, through measuring within-exhibit dyadic conversation and post-exhibit reflection. Children performed successfully on all three tests of learning; fact recall was the most accessible and self-derivation was the least. Both within and post-exhibit involvement predicted overall learning outcomes; within-exhibit conversational phrases predicted self-derivation performance in particular. The current work provides novel insights into mechanisms that support children's informal learning.

The Self-Narrative Role in the Diagnosis of Motivation to Achieve Personal Success

This study aims to investigate the efficacy of self-narrative as a tool for identifying personality traits conducive to motivation for success. The research employs several methodologies, including the "Readiness for Self-Development" test by V.L. Pavlov, the Achievement Motivation Diagnosis test, and the katathym imaginative psychotherapy motive "Mountain" as a form of self-narrative. Psycholinguistic analysis tools such as the verbosity coefficient, embolism coefficient, and correlation coefficient are utilized. Through empirical analysis of self-narratives, criteria for evaluating motivational potential are established. Quantitative and qualitative analyses of respondent narratives reveal distinct patterns. Coefficients derived from psycholinguistic analysis indicate a correlation between self-narratives and motivation for achievement. Respondents demonstrating motivation for success and readiness for self-development exhibit lower verbosity and embolism coefficients. Conversely, those with a tendency to avoid failure and low readiness for self-development tend to employ narratives rich in superficial language elements. The findings suggest that self-narrative analysis can effectively gauge an individual's motivational tendencies and readiness for personal development. This method holds promise as a tool for identifying and nurturing talent within organizations, particularly in the context of forming a vertical personnel reserve. By understanding the motivational drivers revealed through self-narratives, organizations can better tailor their approaches to talent management and development.

Assessing the virtual reality perspectives and self-directed learning skills of nursing students: A machine learning-enhanced approach

AIM

This study aims to investigate nursing students' perspectives on virtual reality technologies and their self-directed learning skills, specifically focusing on how these variables interact and influence each other in the context of nursing education. We also discern potential disparities in these skills based on descriptive characteristics, using both traditional statistical and advanced machine learning approaches for a comprehensive analysis.

BACKGROUND

Rapid developments in technology, particularly during the Covid-19 pandemic, have brought virtual reality technologies to the forefront of nursing education. However, there is a gap in understanding how nursing students' perceptions of these technological relate to their development of self-directed learning skills.

DESIGN

A descriptive and cross-sectional study design is employed to both quantify nursing students' perspectives on virtual reality in their education and assess their self-directed learning skills. This approach integrates traditional statistical methods with advanced machine learning techniques, with the intention of offering a comprehensive and nuanced analysis to inform future teaching strategies in nursing.

METHODS

The study used a blend of survey scales and a tree-based machine learning model to measure and analyze nursing students' views, attitudes and self-directed learning levels. This dual approach allows for a more detailed assessment of the factors influencing self-directed learning abilities. Traditional statistical techniques were also applied to assess the reliability of the machine learning findings.

RESULTS

Findings reveal that nursing students generally held positive views towards virtual reality technologies and exhibited a high level of self-directed learning skills. Notable differences in self-directed learning skills were influenced by gender on the overall scale (p <0.001), with male students scoring higher than their female counterparts in both specific sub-dimensions and on the overall scale, but not by academic year. The machine learning analysis provided deeper insights into these variations, highlighting subtle distinctions in student demographics that traditional statistical methods did not fully capture.

CONCLUSIONS

The study offers valuable insights into interconnected nature of nursing students' views on virtual reality technologies and their self-directed learning skills. The results support the integration of virtual reality in nursing curriculum programs and underscore the importance of customizing teaching strategies based on insights gained from machine learning analyses. This approach has the potential to substantially improve both the learning experience and the overall quality of nursing education.

[Reflections on the Implications of the Developments in ChatGPT for Changes in Medical Education Models]

Ever since its official launch, Chat Generative Pre-Trained Transformer, or ChatGPT, a natural language processing tool driven by artificial intelligence (AI) technology, has attracted much attention from the education community. ChatGPT can play an important role in the field of medical education, with its potential applications ranging from assisting teachers in designing individualized teaching scenarios to enhancing students' practical ability for solving clinical problems and improving teaching and research efficiency. With the developments in technology, it is inevitable that ChatGPT, or other generative AI models, will be thoroughly integrated in more and more medical contexts, which will further enhance the efficiency and quality of medical services and allow doctors to spend more time interacting with patients and implement personalized health management. Herein, we suggested that proactive reflections be made to figure out the best way to cultivate health professional in the context of New Medical Education, to help more medical professionals enhance their understanding of developments in artificial intelligence, and to make preparations for the challenges that will emerge in the new round of technological revolution. Medical educators should focus on guiding students to make proper use of AI tools in the appropriate context, thereby prevening abuse or overreliance caused by a lack of discrimating ability. Teachers should focus on helping medical students make improvements in clinical reasoning skills, self-directed learning, and clinical practical skills. Teachers should stress the importance for medical students to understand the philosophical implications of the mind-body unity concept, holistic medical thinking, and systematic medical thinking. It is important to enhance medical students' humanistic qualities, cultivate their empathy and communication skills, and continually enhance their ability to meet the requirements of individualized precision diagnosis and treatment so that they will better adapt to the future developments in medicine.

What learning strategies are commonly used by hospital pharmacists in the process of self-directed learning? A multicentre qualitative study

OBJECTIVE

As lifelong learners, hospital pharmacists must continually improve their self-directed learning skills. Reasonable learning strategies have been proven to enhance self-directed learning (SDL) significantly. Therefore, this study aims to investigate the SDL strategies used by hospital pharmacists in depth to provide them with a reference for the development of their SDL skills.

SETTING

The study was conducted in three tertiary hospitals in Henan, China.

DESIGN AND PARTICIPANTS

This study employed a multicentre qualitative design and lasted 12 months. One-on-one interviews and focus group discussions were used to collect data. All interviews were transcribed verbatim, and the interview data were analysed using the thematic analysis method. Purposive sampling was used to select interviewees (n=17) from three tertiary hospitals in Henan province in central China.

RESULTS

After conducting data analysis, we summarised 12 learning strategies related to SDL, which were grouped into four themes: use of information resources, application of cognitive strategies, development of learning plans and use of learning platforms.

CONCLUSION

The findings suggest that classic learning strategies, such as cognitive strategies and the development of learning plans, remain the cornerstones of hospital pharmacists' SDL abilities, while contemporary advances in information technology and changes in learning concepts have enriched the learning resources and learning platforms that are available to hospital pharmacists and have confronted contemporary hospital pharmacists with certain challenges.