آموزش افتراقی ارتقاءیافته به کمک فناوری: یک مرور روایتی (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
اهمیت درنظرگرفتن نیازها و ویژگی های متنوع یادگیرندگان در محیط های یادگیری الکترونیکی امری ضروری است و امروزه با بهره مندی محیط های یادگیری از ابزارهای فناورانه، در کانون توجه پژوهشگران حوزه آموزش قرار گرفته است. پژوهش حاضر در نظر داشته است آموزش افتراقی را به عنوان رویکردی که ملاحظه عمیق تفاوت های یادگیرندگان در محیط های یادگیری را دنبال می کند، در محیط های یادگیری الکترونیکی مطالعه کرده و چالش های اجرایی آن را شناسایی کند و در نهایت به کمک ظرفیت های بستر یادگیری ارتقاءیافته به کمک فناوری، راهکارهایی را برای غلبه بر این چالش ها و اجرای اثربخش آن ارائه نموده است. روش این پژوهش، مرور روایتی بوده و پس از جستجو در منابع اطلاعاتی بر اساس کلیدواژه های معین و بر اساس معیارهای ورود و خروج در نظر گرفته شده، پژوهش های نهایی مورد بررسی قرار گرفتند. یافته های پژوهش، طراحی و سازماندهی زمان بر، نیاز به توانمندی های دیجیتالی معلمان، تنوع و نوسان پروفایل های یادگیرندگان و چالش مدیریت کلاس های آنلاین بزرگ و چالش های سنجش و بازخورد را به عنوان چالش های اتخاذ رویکرد آموزش افتراقی در یادگیری الکترونیکی نشان داد. همچنین پژوهش های بررسی شده به نقش رویکردهای داده محور در آموزش مثل واکاوی یادگیری در ارتقا محیط های یادگیری الکترونیکی و رفع چالش های اجرایی آموزش افتراقی در ابعاد مختلف در آن تأکید داشت. در انتها پیشنهاداتی برای پژوهش های بیشتر در کاربست آموزش افتراقی در یادگیری الکترونیکی و استفاده از ظرفیت داده ها به کمک واکاوی یادگیری برای تسهیل اتخاذ این رویکرد ارائه شده است.Technology-Enhanced Differentiated Instruction: A Narrative Review
Considering the diverse needs and characteristics of learners in e-learning environments is essential, and with the integration of technological tools in learning settings, this has become a focal point of research in the field of education. This study aims to explore differentiated instruction as an approach that deeply considers learners' differences in e-learning environments. It identifies the operational challenges of implementing this approach and ultimately proposes solutions to overcome these challenges by leveraging the capabilities of technology-enhanced learning potential. The methodology of this research was a narrative review, conducted by searching information sources using specific keywords and based on predefined inclusion and exclusion criteria. The findings reveal that the main challenges of adopting differentiated instruction in e-learning include time-consuming design and organization, the need for digital capabilities of teachers, the diversity and fluctuation of learner profiles and the challenge of managing large online classes and the challenges of assessment and feedback. The reviewed research emphasizes the role of data-driven approaches in education, such as learning analytics, in enhancing e-learning environments and addressing the operational challenges of differentiated instruction. In conclusion, suggestions for further research on the application of differentiated instruction in e-learning and the use of data through learning analytics to facilitate the adoption of this approach are presented. Introduction The increasing diversity of learners in educational settings, combined with the rise of online learning, presents unique challenges for educators. To address the varied needs of students, differentiated instruction (DI) has emerged as an effective pedagogical approach, which involves tailoring instruction to meet the diverse needs, interests, and readiness levels of individual learners. However, implementing DI in technology-enhanced learning (TEL) environments introduces several challenges, particularly in online settings where interactions are often less direct, and learning environments are more complex. This study explores these challenges and investigates how learning environment data, particularly through learning analytics (LA), can help educators overcome the hurdles of implementing DI effectively. The potential of TEL to collect and analyze learning data is vast, and this data can be utilized to tailor learning experiences that support DI. This narrative review aims to identify the key implementation challenges of DI in TEL environments and explores how data-driven approaches can help address these issues. DI involves adapting instruction to meet individual learner needs, with widely accepted models such as Tomlinson’s model and Hall’s model that provide frameworks for its implementation. In TEL environments, DI can be implemented through "diffuse approaches," "self-directed learning," and "model-based differentiation." These strategies allow teachers to personalize learning pathways, ensuring that each learner can engage with content that suits to their specific profile. Research has demonstrated that DI can enhance learner engagement, improve learning outcomes, and boost motivation and satisfaction. However, there are some research focusing on the specific challenges and solutions for DI implementation in TEL environments, especially in higher education and professional development contexts. To address this research gap, the following research questions are presented: RQ1: What are the key implementation challenges of DI in TEL environments? RQ2: How can data from the learning environment solve these implementation challenges? This narrative review identifies the challenges of DI implementation in TEL environments and explores how LA can provide solutions to these challenges, enabling more effective DI in online learning contexts.. Method This study employs a narrative review approach to explore the challenges and potential solutions for implementing DI in TEL environments. Narrative reviews are ideal for synthesizing diverse research findings from both quantitative and qualitative studies, allowing for a comprehensive examination of the topic across multiple disciplines. By utilizing critical narrative synthesis, this review integrates findings from various educational contexts to present a broad perspective on DI implementation in TEL settings. A comprehensive search of international academic databases was conducted to identify relevant studies. Search terms included combinations of “differentiated instruction,” “online learning differentiation,” “differentiated instruction challenges,” and “technology-enhanced differentiated instruction.” The search was not limited to any specific timeframe, ensuring that the most relevant studies are captured. Inclusion criteria focused on research that addressed DI at various educational levels and in different contexts, particularly those that investigated the use of TEL. Thematic analysis was used as the primary method of data analysis to identify recurring challenges faced by educators when implementing DI in online learning environments. Specific codes were assigned to sections of studies discussing these challenges, and emerging themes were grouped to form a comprehensive understanding of the key obstacles. This iterative process allowed for refinement of the codes and categories, ultimately identifying five major challenges in DI implementation in TEL environments. After identifying these core challenges, the study explores how learning analytics can be employed to address these issues and support the successful implementation of DI in TEL environments. Findings Research Question 1: What are the key implementation challenges of DI in TEL environments? This review identified five major challenges that educators are faced with when implementing differentiated instruction (DI) in online learning environments: Time-Consuming Design and Organization: Implementing DI requires significant time and resources due to the need to create and manage multiple sets of materials that cater to diverse learner profiles. The challenge is intensified in online settings, where learner diversity is more profound. Need for Teachers' Digital Competencies: Teachers must have strong digital skills to implement DI effectively. They need to be proficient in using technology to create personalized learning experiences and engage learners with interactive tools. Diversity and Variability in Learner Profiles: Learner profiles, including interests and readiness levels, change constantly. This variability makes it difficult for teachers to adapt instruction in online environments, where interactions are less direct. Managing Large Online Classes: Meeting the diverse needs of learners in large online classes is resource-intensive and demands careful planning to ensure all learners receive personalized instruction. Challenges in Assessment and Feedback: Providing timely, personalized feedback is difficult in online environments. Teachers require effective tools, often dependent on learning analytics, to assess progress and deliver relevant feedback. Research Question 2: How can data from the learning environment address these implementation challenges? Learning analytics (LA) offers promising solutions for addressing the challenges of DI in TEL environments. LA systematically collects and analyzes learner data to inform instructional decisions and personalize learning experiences. Providing Timely Data for Personalized Learning Design: LA automates data collection and analysis, allowing teachers to quickly visualize learner performance and guide content creation, reducing the time needed for personalized instruction. Facilitating Teachers' Use of Digital Platforms: LA provides user-friendly tools that simplify data interpretation, allowing teachers to adjust instruction without needing advanced technical skills. Handling Learner Profile Diversity: LA helps educators track and analyze learner behaviors, enabling them to group learners with similar profiles and tailor instruction to meet their specific needs. Improving Management of Large Online Classes: LA offers real-time insights into learner performance, allowing teachers to manage diverse learner needs in large classes more effectively. Enhancing Assessment and Feedback: LA automates feedback mechanisms, providing timely, personalized suggestions and allowing teachers to continuously assess learners and target support where needed. Result and Discussion This narrative review explored the challenges of implementing DI in TEL environments and examined how data-driven approaches, particularly LA can help address these issues. This study identified five key challenges: the time-consuming nature of designing and organizing personalized content, the need for advanced digital competencies among educators, the diversity and variability of learner profiles, the difficulty in managing large online classes, and the complexities of assessment and feedback in online settings. LA offers promising solutions to these challenges by automating data collection and analysis, providing real-time insights into learner behavior, and simplifying the use of digital tools. This allows educators to tailor more effectively instruction to individual learners and manage large groups with diverse needs. Additionally, LA enhances the feedback process by offering continuous, personalized evaluations based on real-time data. While implementing DI in TEL environments is resource-intensive, LA can streamline many aspects of this process, improving both efficiency and effectiveness. Further research is required to assess the long-term impact of LA on learner outcomes and its scalability in various educational contexts.
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