open and distance learning

Academic writing development in open and distance learning (ODL) environments remains challenging because students must independently regulate complex writing processes while receiving limited opportunities for continuous interaction and feedback. Existing digital learning platforms often emphasize assignment submission rather than supporting writing development as an iterative process involving planning, feedback utilization, reflection, and revision. This study aimed to develop and evaluate SIM-Aril as an online portfolio-based self-regulated feedback platform for supporting academic writing development in an ODL context. This study employed a Research and Development (R&D) design involving needs analysis, platform development, validation, implementation, and evaluation. Data were collected from 122 students and 38 tutors through self-regulated writing questionnaires, tutor competency questionnaires, expert evaluation, and qualitative responses. Quantitative data were analyzed using descriptive statistics, reliability analysis, correlation analysis, regression analysis, and exploratory factor analysis, while qualitative data were analyzed thematically. The findings demonstrate that SIM-Aril supported academic writing development through the integration of digital portfolio assessment, tutor scaffolding, and student self-regulated writing processes. Students demonstrated strong engagement in revision, feedback utilization, metacognitive monitoring, and other writing regulation activities. Tutor evaluation indicated that academic writing supervision represented an important component supporting SIM-Aril implementation. The integrated findings show that SIM-Aril functions not merely as a digital submission platform but as a self-regulated feedback ecosystem that connects learner autonomy, instructional support, and formative feedback. This study contributes theoretically by extending digital assessment research through a model that integrates individual self-regulation, socially shared regulation, and feedback literacy within technology-supported academic writing environments. Practically, the findings suggest that effective digital assessment in ODL should be designed to support learning processes rather than only evaluate final outcomes.

The University of South Africa (UNISA) is the largest higher education institution (HEI) in Africa. In fact, UNISA is one of the largest and leading open-distance e-learning (ODeL) institutions in the world and is reputable for its commitment to providing increased access to quality education and flexible teaching. Therefore, UNISA presents a unique context for exploring teacher education through flexible learning. To this end, the current research was conducted between February and May of 2025 and explored the role of flexible learning in teacher education at an influential model in the Global South. The rationale for this research was grounded in the need to address educational challenges in Africa through innovative teaching methods. Employing systematic document analysis and governed by the principles of grounded theory in the collection and analysis of data, this study aimed to explore UNISA’s provision of flexible teacher education. The findings revealed that flexible teacher education in Africa is a necessity and a complex undertaking. It is shaped by demographic pressures, economic constraints, historical inequalities, and crisis events such as the COVID-19 pandemic. Flexible learning expands access, reduces costs, and offers opportunities for curriculum transformation. Its effectiveness, however, is constrained by systemic challenges, including digital inequalities, resistance to pedagogical change, and limitations in institutional capacity. A key contribution of this research is the development of an emerging theory that reveals that flexible education is a balancing act between expanding access and maintaining quality.

Introduction Generative artificial intelligence (GenAI) is increasingly used by students to obtain explanations, generate ideas, improve written responses and prepare assessment tasks. However, limited evidence exists on how students in open-distance alternative-access programmes experience GenAI in mathematics assessment. Methods This qualitative study examined how 27 Higher Certificate students at a South African open and distance learning institution described the role, benefits and limitations of GenAI while preparing fraction-related portfolio activities. Data were collected via a single open-ended questionnaire item, completed voluntarily after all assessment activities had been submitted. The responses were analysed using reflexive thematic analysis. Results Four overlapping themes were identified: support for understanding and approaching tasks, support for constructing written responses, conditional trust and evaluative engagement, and non-use, resistance and ambiguous engagement. Students reported that GenAI assisted with clarification, examples, organisation, and language, but they also described outputs they perceived as inaccurate, overly general, or insufficiently explained. Ten participants expressed concerns about reliability or described checking, adapting, limiting or rejecting GenAI use, although the study did not verify the quality of these practices. Discussion The findings suggest that the educational value of GenAI is shaped by students' capacity to exercise judgement and retain responsibility for the reasoning represented in their work. Verification is therefore positioned as a potentially important epistemic practice in GenAI-supported mathematics assessment. The study recommends explicit discipline-specific guidance and assessment designs that make students' mathematical reasoning visible.

مقدمه: هوش مصنوعی مولد (GenAI) به طور فزاینده‌ای توسط دانشجویان برای دریافت توضیحات، تولید ایده‌ها، بهبود پاسخ‌های نوشتاری و آماده‌سازی وظایف ارزیابی مورد استفاده قرار می‌گیرد. با این حال، شواهد محدودی درباره تجربه دانشجویان در برنامه‌های دسترسی جایگزین آموزش باز و از راه دور در زمینه استفاده از GenAI در ارزیابی ریاضی وجود دارد. روش‌ها: این مطالعه کیفی به بررسی نحوه توصیف نقش، مزایا و محدودیت‌های GenAI توسط ۲۷ دانشجوی Higher Certificate در یک مؤسسه آموزش باز و از راه دور در آفریقای جنوبی هنگام آماده‌سازی فعالیت‌های پرتفوی مرتبط با کسرها پرداخت. داده‌ها از طریق یک سؤال بازپاسخ در پرسشنامه که به صورت داوطلبانه پس از اتمام تمامی فعالیت‌های ارزیابی تکمیل شد، جمع‌آوری گردید. پاسخ‌ها با استفاده از تحلیل تماتیک بازتابی مورد بررسی قرار گرفتند. نتایج: چهار تم همپوشان شناسایی شد: حمایت برای درک و رویکرد به وظایف، حمایت در ساخت پاسخ‌های نوشتاری، اعتماد مشروط و مشارکت ارزیابانه، و عدم استفاده، مقاومت و مشارکت مبهم. دانشجویان گزارش دادند که GenAI در زمینه شفاف‌سازی، ارائه مثال، سازماندهی و زبان کمک‌کننده بوده است، اما همچنین خروجی‌هایی را توصیف کردند که آن‌ها را نادرست، بیش از حد کلی یا فاقد توضیح کافی می‌دانستند. ده نفر از شرکت‌کنندگان نگرانی‌هایی درباره پایایی ابراز کردند یا به بررسی، تطبیق، محدودسازی یا رد استفاده از GenAI اشاره نمودند، اگرچه این مطالعه کیفیت این اقدامات را تأیید نکرد. بحث: یافته‌ها نشان می‌دهد که ارزش آموزشی GenAI توسط توانایی دانشجویان در اعمال قضاوت و حفظ مسئولیت نسبت به استدلال ارائه‌شده در کارشان شکل می‌گیرد. بنابراین، راستی‌آزمایی به عنوان یک عمل معرفتی بالقوه مهم در ارزیابی ریاضی با حمایت GenAI مطرح می‌شود. مطالعه حاضر راهنمایی صریح و خاص رشته و طراحی ارزیابی‌هایی که استدلال ریاضی دانشجویان را آشکار می‌سازد، توصیه می‌کند.