Adaptive Learning

In the video Creating Multiple Paths for Learning (1997), Carol Ann Tomlinson, noted differentiation expert, says that differentiating instruction means that the teacher anticipates the differences in students' readiness, interests, and learning profiles and, as a result, creates different learning paths so that students have the opportunity to learn as much as they can as deeply as they can, without undue anxiety because the assignments are too taxing—or boredom because they are not challenging enough. Differentiated instruction theory can be used to create better problem-solving learning approaches by providing personalized feedback and also the use of natural language dialogs will prove beneficial to the learner who uses the problem-solving approach to fulfill his learning objectives. Different instructional designs should be integrated and hybrid approaches to learner must be created and also evaluated to understand their usability and applicability. “Differentiation can be accurately described as classroom practice with a balanced emphasis on individual students and course content,” write Carol Ann Tomlinson and Marcia B. Imbeau in their book Leading and Managing a Differentiated Classroom (2010). The need for the balanced emphasis is evident through the diversity students bring to the classroom: “Students differ as learners in terms of background experience, culture, language, gender, interests, readiness to learn, modes of learning, speed of learning, support systems for learning, self-awareness as a learner, confidence as a learner, independence as a learner, and a host of other ways” (p. 13). Most important, these differences will “profoundly affect how students learn and the nature of scaffolding they will need at various points in the learning process.”

The term adaptive learning refers to a nonlinear approach to online instruction that adjusts to a student's needs as the student progresses through course content, resulting in a customized experience for the learner based on prior knowledge. This concept is emerging in the field of online learning. According to a survey of 338 chief information officers and senior campus information technology (IT) officials, adaptive learning technologies have great potential for improving student outcomes (Green, 2016). The emergence of personalized adaptive learning is due to the rise of big data technology, data is generated in more and more ways and faster and faster speed, which has spawned Data-Intensive Science, the fourth scientific research paradigm (Hey et al. 2009). Under the influence of data-intensive science, personalized adaptive learning has become the fifth-generation educational technology research paradigm (Zhu and Shen 2013). Based on big data, it has become an important part of a digital learning environment (Zhu and Guan 2013)

References

file:///C:/Users/ADMIN/Downloads/3_Fareeha_Rasheed_VSRDIJTNTR_13743_Research_Paper_9_4_April_2018.pdf

https://pdo.ascd.org/LMSCourses/PD11OC115M/media/DI-Intro_M1_Reading_What_Is_DI.pdf

https://joe.org/joe/2018september/pdf/JOE_v56_5a5.pdf