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Lessons Learned From Academic Women Researchers Engaged in Training Needs Assessment for Developing Research and Publishing Skills
academic women researchers empowerment training needs assessment writing for publication...
Despite progress made in recent years, women continue to be underrepresented in academic publishing. We aim to share insights from academic women researchers who participated in the Training Needs Assessment for developing their writing for publication skills in an Open Distance Learning institution in South Africa. The research questions that guided the study were: a) What specific challenges do academic women researchers face in developing research and publishing skills? b) What motivated academic women researchers to participate in a writing project? c) What type of support do academic women researchers identify as essential for advancing their research and publishing skills? The data were collected through an initial face-to-face meeting, followed by a Training Needs Assessment from eight purposively chosen participants in a case study design. The findings indicate participants’ challenges of time constraints, lack of confidence, and knowledge as obstacles that hindered their publishing. Despite their challenges, women researchers reported their motivation to participate in the writing project for career advancement, personal development, academic recognition, and their inspiration to publish their research work. The study found that women researchers required writing support, peer collaboration, mentorship, and institutional support to improve their writing for publishing skills. Supporting academic women researchers with focused training, engaging them in collaborative networks, and developing gender-sensitive policies is crucial for promoting equity, breaking down barriers, and ensuring their academic and professional success.
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A Mixed-Method Exploration of University Students’ Views about Reality and Knowledge: Combining Semantic Analysis of Textual Data and Quantitative Survey Research
cluster analysis concept maps leximancer semantic network analysis...
Within the context of investigating belief systems, this work exemplifies a mixed-method approach. Two approaches are utilized to explore the philosophical, ontological, and epistemological assumptions that university students foster regarding the relationships between knowledge and reality. In the first step, written materials that elaborated on the matter at hand were subjected to content analysis with the assistance of Leximancer, a software that recognizes themes and concepts and turns textual data into concept maps that express networks of meaning. The second step involved conducting a cluster analysis on the data obtained from the questionnaire to identify distinct groups of participants who shared consistent epistemological viewpoints. The results obtained from the two approaches are in agreement and shed light on the prevalent epistemic inclination that favors a constructivist viewpoint. Discussion on the ramifications of the findings, as well as the methodological issues that are pertinent to the present illustration, is provided.
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Pedagogical Influence of AI-Chatbots on Learning Outcomes: A Systematic Review
ai chatbots learning outcomes pedagogical influence systematic review...
In recent years, significant developments have occurred in AI-based chatbots that have been effectively deployed in the educational field. However, given the novelty of this technology, descriptive analyses remain scarce. Although many review studies have focused on the effectiveness of chatbots, they generally present broad results, and only a few have addressed the impact of this technology on learning outcomes. The present study examines the educational implications of AI chatbots on various learning outcomes through a post hoc analysis conducted in accordance with PRISMA principles. It aims to aggregate and analyze findings from studies that examined the use of chatbots and their impact on specific learning outcomes. A total of 26 studies were selected from a pool of 6,721 published between 2021 and 2024 and indexed in the Scopus and Web of Science databases. Data analysis was conducted using the Newcastle-Ottawa Scale (NOS) for Education. The results revealed that AI-chatbot technology has a positive influence on several learning outcomes, including academic achievement, motivation, self-assessment, engagement in learning, self-efficacy, and language learning, among others. The studies also detailed the methodologies and tools employed in these investigations. The study also offers insights into how intelligent chatbots can be leveraged to enhance various learning outcomes.
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