Differentiation through 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.”

Adaptive learning and advantages/why Adaptive learning

According to Murray & Pérez, 2015. ‘’ 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)’’.

Educators have long known that learning is improved when instruction is personalized -- adapted to individual learning styles. In fact, some argue that advocacy for adaptive instruction dates back to antiquity (Lee & Park, 2008). Modern views of adaptive learning theory, however, are rooted in the work of contemporary educational psychologists. Cronbach (1957) theorized that learning outcomes are based on the interaction between “attributes of person” and treatment variables. He advocated for differentiating instruction (treatment) to a person’s cognitive aptitude. The findings of his early research were inconsistent, leading him to surmise that unidentified interactions existed. His original hypothesis forms the foundation for adaptive learning; he subsequently extended his model to include cognition and personality (Cronbach, 1975). Educators should, he states, “find for each individual the treatment to which he can most easily adapt” (Cronbach, 1957, p.679).

Adaptive learning can:

-Can be Customized to Fit All Learning Levels

-Provides Real-time Feedback

With adaptive learning technology:

-Accelerates Students’ Progress

-Keeps Students Engaged and Motivated

Students receive immediate response to whatever they are working on.

The challenges faced by the students are easily identified.

Students do not need to take tests every time to identify the information they have retained

Adaptive learning technology employs the method of modifying the curriculum to help every student in the class access information according to their intellectual capabilities.

Adaptive learning systems

Adaptive learning systems represent a plethora of pedagogical and technological approaches that are difficult to categorize. Lee and Park (2008) delineate ALSs by instructional level. At the macro-level, instruction is adapted by altering instructional goals, delivery systems, or curriculum, enabling adaptation at many dimensions including navigation, assessment, and presentation. Examples include platforms that support instructor creation and development of adaptive learning environments. Mid-level systems facilitate the adaptation of instructional strategies. A simple example of these systems is one that modifies content presentation by medium (audio, visual, video) based on learning preferences indicated by students. At the micro-level, instruction is adapted in real-time as student learning needs are diagnosed and instructional treatments prescribed. These systems employ on-task measurements of student behavior, such as response errors and response latencies, which result in variation of the amount or sequence of content presented to the student.

Example of adaptive learning

https://elearningindustry.com/adaptive-learning-for-schools-colleges

Conclusion

According to Murray and Perez, ‘’Adaptive learning is touted as a potential game-changer in higher education, a panacea with which institutions may solve the riddle of the iron triangle: quality, cost, and access. Though the research is scant, this study and a few others like it indicate that today’s adaptive learning systems have negligible impact on learning outcomes, one aspect of quality’’. There is also evidence that adaptive systems positively impact other aspects of quality such as student persistence and engagement (Jarrett, 2013; Zimmer, 2014).

References

S. Adams Becker, M. Cummins, A. Davis, A. Freeman, C. Hall Giesinger, V. Ananthanarayanan, NMC Horizon Report: 2017 Higher Education Edition (The New Media Consortium, Austin, 2017)

E. K. Adu, & D. C. C. Poo (2014). Smart Learning: A New Paradigm of Learning in the Smart Age. http://www.cdtl.nus.edu.sg/ Tlhe/tlhe2014/abstracts/aduek.pdf. Accessed 01 June 2019

L.W. Anderson, D.R. Krathwohl, B.S. Bloom, A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom's Taxonomy of Educational Objectives:

Allyn & Bacon (2001) ASCD. (2018). Differentiated Instruction. http://www.ascd.org/research-a-topic/differentiated-instruction-resources.aspx. Accessed 01 June 2019 BECTA. (2007). Personalising Learning: The Opportunities Offered by Technology. http://archive.teachfind.com/becta/ feandskills.becta.org.uk/display806e.html?resID=31571. Accessed 01 June 2019 C. Binder, Precision teaching: Measuring and attaining exemplary academic achievement. Youth Policy 10(7), 12–15 (1988) DfES.(2006).2020 Vision: Report of the Teaching and Learning in 2020 Review Group. https://dera.ioe.ac.uk/6347/1/6856-DfESTeaching%20and%20Learning.pdf. Accessed 01 June 2019 Dreambox. (n.d.) Personalized Learning. http://www.dreambox.com/personalized-learning. Accessed 01 June 2019 EDUCAUSE. (2016). Adaptive Learning Systems: Surviving the Storm. https://er.educause.edu/articles/2016/10/adaptivelearning-systems-surviving-the-storm. Accessed 01 June 2019

Green-Lerman, H. (2015). Visualizing Personalized Learning. https://www.knewton.com/resources/blog/adaptive-learning/ visualizing-personalized-learning/. Accessed 01 June 2019 B. Gros, The design of smart educational environments. Smart. Learn. Environ. 3(1), 15 (2016)

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

http://www.inform.nu/Articles/Vol18/ISJv18p111-125Murray1572.pdf

https://www.youtube.com/watch?v=ajd10OK6kHA

https://www.youtube.com/watch?v=N6aYR0uCe9o

https://www.youtube.com/watch?v=YR5R37QNPco

https://www.youtube.com/watch?v=YWgsYGUzvMg

https://www.melimu.com/home/

https://library.educause.edu/resources/2017/1/7-things-you-should-know-about-adaptive-learning