E-learning

ADAPTIVE LEARNING

Adaptive learning is a teaching method that uses computers and technology to facilitate comprehension and retention based on the unique needs of the learner.

Adaptive learning is a computer-based or online educational system that modifies the presentation of material in response to student performance. Best-of-breed systems capture fine-grained data and use learning analytics to enable human tailoring of responses.

The term ADAPTIVE came from the original work used in Engineering Control Theory where in the Control System will adapt to behave appropriately according to the input signal to produce the output signal.

It is an educational method which uses computers as interactive teaching devices, and to orchestrate the allocation of human and mediated resources according to the unique needs of each learner.

Adaptive learning or intelligent tutoring has its origins in the artificial-intelligence movement and began gaining popularity in the 1970s. At that time, it was commonly accepted that computers would eventually achieve the human ability of adaptivity. The history of adaptive learning rooted in cognitive psychology, beginning with the work of behaviorist B.F. Skinner in the 1950s, and continuing through the artificial intelligence movement of the 1970s.

Skinner constructed a teaching machine that focused on effectively teaching new concepts instead of reinforcing memorization. The machine worked by allowing the student to practice new concepts by answering questions. If the question was answered correctly, feedback and positive reinforcement was given. If the answer was wrong, instead of just having the student try again, smaller steps were taken towards the right answer through a series of small hints. This allowed students to not only study at their own pace, but also receive immediate feedback so they could see how they were doing.

A critical part of education is also developing students’ ability to interact and work with others—from the teachers who guide them and spark their interests and passions to their peers with whom they work, learn and teach. Learning is ultimately a social experience, as it builds people into more mature social actors able to participate in civic society and lead productive lives.

But adaptive learning is a powerful force to make those pursuits more effective and efficient. Additionally, this technology can accelerate our knowledge of what learning experiences work best, for which students, in which circumstances, so that educators can adapt to a reality in which they can help all children find their passions and reach their fullest potential.

The phrase “adaptive learning” is an umbrella term that applies to an incredibly broad range of technologies and techniques with very different educational applications. The common thread is that they all involve software that observes some aspect of student performance and adjusts what it presents to each student based on those observations. In other words, all adaptive software tries to mimic some aspect of what a good teacher does, given that every student has individual needs.

Adaptive learning combines the previous generations of rule-based, simple machine learning, and deep learning approaches to machine intelligence. Human analysts are optimally engaged in making the machine intelligence smarter, faster, and easier to interpret, building on a network of the previous generations of machine intelligence. Artificial intelligence (AI) is the intelligence exhibited by machines or software. It is also the name of the academic field of study which studies how to create computers and computer software that are capable of intelligent behavior.

Adaptive learning makes content dynamic and interactive, placing the student at the center of his or her individual learning experience. The platform monitors how the student interacts with the system and learns, leveraging the enormous quantities of data generated by a student’s online interactions with ordinary (textbook-like) and extraordinary (game- and social-media-like) content, with teachers and peers, and with the system itself. It assesses not only what a student knows now, but also determines what activities and interactions, developed by which providers, delivered in what sequence and medium, most greatly increase the possibility of that student’s academic success.

One of the most important education innovations that have come from adaptive learning is the ability to immediately change instruction based upon a student’s knowledge. As each student works with the program, the technology will pick up on what he or she is mastering or still struggling with and adjust instruction in real-time. In this way, learning is optimized because the adaptive learning program can change its approach on an individual level to make sure students are mastering concepts before moving on to more difficult material.

Educational adaptive systems model adapts to individual’s preferred learning styles and provide constant feedback to help the learner improve. What is needed to make this happen is to access how Student is behaving (INPUT), Behavior Pattern of the Learner and understand the Performance of the learner and Provide them Immediate Feedback.

As children interact with the Adaptive Learning System they generate data that collates in the Result Vault, building a detailed picture of their progress over time. Because the system is always testing, analyzing and tracking students, it readily facilitates assessment of both their historical progress and real-time results.

With adaptive learning, the method and pace of instruction is customized for each individual student, which could improve their chances of truly understanding new academic concepts. For example, if a mathematics student makes a mistake with the specific step of factoring polynomials while attempting to solve a polynomial equation, so the program provides the student with extra hints and supplemental practice problems on that step.

Many K-12 students today are ‘digital natives,’ meaning the technologies that are so commonplace today have always been a part of their lives. As a result, they are particularly tech savvy, and may become more engaged in their lessons if given the chance to spend part of class time on the computer using adaptive learning programs.

With adaptive learning technology, students’ answers are analyzed in real time and the software adjusts instruction accordingly. In this way, kids are able to work at different paces and achieve the best possible academic outcomes. It's in this way that adaptive learning tools go beyond merely tracking whether or not a student answers questions correctly.

Most often the adaptive learning is confused with the adaptive testing. The adaptive testing is a method in which the difficulty level of questions is adjusted continuously to ascertain the competency level of a learner. The questions are posed to the learner, on a given subject matter, with known level of difficulty, say medium level of difficulty and if the student answers questions correctly then the difficulty level is increased. The level of difficulty is increased in each questions posed until the learner starts not answering questions. Then the difficulty level is reduced. By going over several related subject matter areas after sufficient number of questions/answer sessions a score is calculated for the student and then he is put on a percentile basis on the scale by the adaptive testing agency who already have a corpus of normalized data with percentile distribution.

In adaptive testing based adaptive learning systems the content level of difficulty and explanation is varied based on the question/answer set. However in such systems there is no distinct pedagogy that is used for the variation of content presentation to the user for cognitive opportunity enhancement.

In true, adaptive learning system, first requirement is to have a pedagogical framework for the presentation of content in three or more learning paths and then there is assessment engine that will provide continuous feedback and rotation of learners through the learning path to reach a desired competency level with desired learning outcome.

Hence most of the claims made by the adaptive learning systems that are purely based on adaptive testing do not provide sufficient distinction of content in terms of cognitive learning strategies to be termed as adaptive learning systems. We need to dispel the myth that adaptive testing based content presentation systems are adaptive systems and do not match with the learning preference of the individual learners.

The Adaptive Learning Systems on the other had represent knowledge in distinct cognitive pathways such as apprentice, incidental, inductive deductive and discovery -- providing same content in a different contextual framework thereby providing significant cognitive opportunity to learn. Also in the education adaptive learning systems the feedback is given in a different learning pathway to provide another perspective on the same problem.

Therefore, the an authentic adaptive learning systems is not domain specific and can provide better learning for both scientific disciplines with deterministic answers to domains where the answers are more based interpretation style and there no correct answer.

This is an incredible personalized learning system that adapts to all learning capabilities. This technology saves educators the entire process of identifying the different levels of learners and modifying course content and instructions accordingly. When students start working with adaptive learning technology, it picks up what different students are struggling with and what they are good at. Once that is done, it can adjust the instructions in a way that will benefit all kinds of learners. And the entire process takes place in real-time.

The Adaptive Learning Systems on the other had represent knowledge in distinct cognitive pathways such as apprentice, incidental, inductive deductive and discovery providing same content in a different contextual framework thereby providing significant cognitive opportunity to learn. Also in the education adaptive learning systems the feedback is given in a different learning pathway to provide another perspective on the same problem

This style of learning ensures that no student lags behind. It provides additional resources to bring every slow learner up to speed. With adaptive learning, students get to understand the concepts completely before moving on to the next or more difficult one. Students are less likely to lose focus if feedback is immediate and they can quickly self-correct. A continuously adaptive learning system is able to deliver personalized feedback to both multiple choice and free response questions quickly — that is, instantaneously or near instantaneously. The result is pacing that is conducive to risk-taking, experimentation, iterative development, and rapid learning.

Therefore, the an authentic adaptive learning systems is not domain specific and can provide better learning for both scientific disciplines with deterministic answers to domains where the answers are more based interpretation style and there no correct Benjamin Bloom chaired a committee in 1956 to come up with taxonomy that will categorize the learning objectives for the courses. The important contribution was to include three factors in the learning objective cognitive, affective and psychomotor activities to reach a given learning objective. The taxonomy included a set of verbs or an action items that required teachers to design their lessons and instruction to include all three learning modalities knowing, feeling and doing. There have been several revisions and additions to the Bloom's taxonomy, but it is perhaps one of the most influential taxonomy used widely by the instructional designer and curriculum designer in

Adaptive learning technology lets students know whether they are rushing through a chapter that requires some more time and attention according to their level of comprehension and retention. This way, jumping ahead in a chapter at the risk of less retention is reduced and students get to understand and remember the course material better. As a result, memory serves better at the time of examinations. With Adaptive Pathways, when students hit a roadblock, you can direct them to resources that help remediate their misconception. Or when students successfully grasp a concept, you can ‘fast-track’ those students and offer more content to stretch their knowledge. Adding Adaptive Pathways to your courseware enables you to better support at-risk students, motivate high achievers and get the best out of every student.

With adaptive learning technology, every student’s learning requirements are attended to, no matter how varied those are. It is the right amount of help they need to cross the hurdles and see their efforts reap results. Once the outcomes start getting better, they would automatically be drawn towards learning more. This would decrease the dropout rate immensely.

In project 3G, adaptive tools can apply a deep understanding of student behavior and learning. Through the data mining process, learning patterns inevitably arise, allowing adaptive tools to use insights from the aggregate to become even more powerful and precise; the more students use an adaptive learning engine, the "smarter" it becomes. Our Adaptive learning systems endeavor to transform the learner from passive receptor of information to collaborator in the educational process.

Every student is unique in his or her strengths and challenges. Each student differs in their tastes. Students differ from one another in a wide variety of ways, including the types of instruction to which they respond best (learning styles), the ways they approach their studies (orientations to studying and approaches to learning), and their attitudes about the nature of knowledge and their role in constructing it (levels of intellectual development).

VIDEO SERIES by Dr. Nish Solwalker BASED On his BOOK [2010-2011]

He is the one who developed pedagogical framework of “The Leaning Cube” combining media, models and interactivity to develop adaptive learning technology and interfaces. It is called the BRAIN BASED ADAPTIVE LEARNING Technology. Definitely something we all should dig deeper.

“Changing the Interface of Higher Education with Revolutionary Learning Technology”

1. Introduction to Personalized Adaptive Learning Video Series [April 2010] : https://youtu.be/Wh_SJNyLotQ?list=FLceIP70tJjnMfpCUPDGXV7Q

• Dr. Nish Sonwalkar (Sc.D., MIT) author of the book "Changing the Interface of Higher Education with Revolutionary Learning Technology" provide introduction to the book and the concept of individualized learning.
• Ref. Sonwalkar, N. "Changing the Interface of Higher Education," iUniverse, NY, Introduction

2. Adaptive Learning 1: Changing the Technology Interface of Education [April 2010] : https://youtu.be/jyxFhGgXk5Y?list=FLceIP70tJjnMfpCUPDGXV7Q

• This video presents the concept of changing the interface of higher education. With the development of new technological interfaces there is need for the development of a new pedagogical framework.
• Ref. Sonwalkar, N. "Changing the Interface of Higher Education," iUniverse, NY, Chapter 1

3. Adaptive Learning 2: The Pedagogical Framework "Learning Cube" [April 2010] : https://youtu.be/BUVDubKL1Yw?list=FLceIP70tJjnMfpCUPDGXV7Q

• Dr. Nish Sonwalkar (Sc.D., MIT) provides a framework for online education that combines multimedia, learning models, interactivity including social media interaction. The model represents the "Learning Cube" framework that provides dimensions of media, models and interactivity as a cubical learning space where one can create individualized learning experience with adaptive learning.
• Ref. Sonwalkar, N. "Changing the Interface of Higher Education," iUniverse, NY, Chapter 2

4. Adaptive Learning 3: Pedagogical Instructional Design [April 2010]

• Dr. Nish Sonwalkar (Sc.D., MIT) describes the d... In this video, Dr. Nish Sonwalkar (Sc.D., MIT) describes the development of adaptive pathways for learning by creating five different instructional strategies to accommodate individual preferences.
• Ref. Sonwalkar, N. "Changing the Interface of Higher Education," iUniverse, 2004, Chapter 3

5. Adaptive Learning 4: Designing Courses for Adaptive Learning [April 2010] : https://youtu.be/-ksnoznmHUc?list=FLceIP70tJjnMfpCUPDGXV7Q

• Dr. Nish Sonwalkar (Sc.d., MIT) explains differentiated instructions that can be used to encourage five pedagogical models to enhance learning performance. The learning cube framwork allows creation of course structures that confirm to proposed learning models allows creation of courses with multiple learning styles.
• Ref. Sonwalkar, N."Changing the Interface of Higher Education," iUniverse, NY, Chapter 4.

6. Adaptive Learning 5: The Adaptive Learning Systems [April 2010] : https://youtu.be/Aco7pki_diE?list=FLceIP70tJjnMfpCUPDGXV7Q

• In this video, Dr. Nish Sonwalkar (SC.D., MIT) presents the implementation of adaptive learning using five different learning models and collecting statistics on learning performance based on the diagnostic assessments. The system that adapts to individual learning pathway and provides feedback to improve the learning performance.
• Ref. Sonwalkar, N."Changing the Interface of Higher Education," iUniverse, NY, Chapter 5.

7. Adaptive Learning 6: Evaluation and Assessment Methods [April 2010] : https://youtu.be/S6CoZyG-Lb4?list=FLceIP70tJjnMfpCUPDGXV7Q

• Dr. Nish Sonwalkar (Sc.D., MIT) presents the methods of evaluation and assessments for online courses and programs. The evaluation of online course requires a multi-dimensional approach. Dr. Sonwalkar presents a framework of pedagogical effectiveness index, which incorporates the dimensions of multi-media, learning models and interactivity to assess and rate effectiveness of online courses.
• Ref. Sonwalkar, N. "Changing the Interface of Higher Education," iUniverse, NY Chapter 6

8. Adaptive Learning 7: Improving Individual Learning Performance [April 2010] : https://youtu.be/t_oIY_2m0T4?list=FLceIP70tJjnMfpCUPDGXV7Q

• Dr. Nish Sonwwalkar (Sc.D., MIT) presents relationship between personality type and learning strategies to optimise individual learning performance.

9. Adaptive Learning 8: Higher Retention and Degree Completion [April 2011] : https://youtu.be/H2IQvWfQQ9M?list=FLceIP70tJjnMfpCUPDGXV7Q

• Dr. Nish Sonwalkar in this video presents his view on why the current online learning systems lead to low completion rates. The use of personalized adaptive learning systems can lead to higher completion by facilitating different learning strategies for motivation, real-time feedback to keep students engaged and opportunity to improve with each learning cycle. The adaptive learning systems has been observed to provide very high retention and degree completion rates.

10. Adaptive Learning 9: Adaptive Mobile Learning [April 2010] : https://youtu.be/eDVd_vNWicM?list=FLceIP70tJjnMfpCUPDGXV7Q

• Dr. Nish Sonwalkar (Sc.D., MIT) is presenting re... In this video Dr. Nish Sonwalkar (Sc.D., MIT) is presenting recent developments in Mobile Learning. This presentation was made for an event hosted at face-book for the large number of friends and fans of Dr. Sonwalkar. He is pioneer in the field of Adaptive Learning and has now created technology called Adaptive Mobile Learning (AMOL).

11. Adaptive Learning 10: Adaptive Personalized Learning Systems [June 2011] : https://youtu.be/lIVaY3Qci6M?list=FLceIP70tJjnMfpCUPDGXV7Q

• Dr. Sonwalkar describes four components of educational adaptive learning systems. The four components are - pedagogical framework with distinct learning strategies, learning trajectory, evolution of effectiveness of learning trajectory and intelligent revision for reaching desired learning outcome. These are four essential components that are necessary to create any adaptive and/or personalized learning systems for the online education.

NEWER VIDEOS by Dr. NISH SONWALKER (More Adapted to Newer Technologies) [2011-2012]

12. What is Pedagogy? June 2011 : https://youtu.be/jkoRR670fj8?list=FLceIP70tJjnMfpCUPDGXV7Q

• Dr. Sonwalkar describes the term "Pedagogy." The term does not refer to presentation of content with evaluation and few information bits. He explains that the pedagogy is the process of presenting content in the context of learning strategies that connect with a cognitive process. It now generally refers to creation of effective lesson plan for classroom instruction and online education.

13. Brain-based Adaptive Learning for Developing Creative Thinking – Keynote [July 2011] : https://youtu.be/OCrMxsUp_KQ?list=FLceIP70tJjnMfpCUPDGXV7Q

• Keynote speech delivered by Dr. Nish Sonwalkar (Sc.D., MIT) at the Research :Leaders Conference organized by NSU on July 20, 2011.
• The creative thinking is often considered a realm of poets, singers, artists, designers and mathematician, such as, Einstein, Picasso, Stravinsky and Gandhi. Recent neurological research shows that creativity is an acquired skill that can be developed by a systematic divergent learning approach. The creative thinking is an essential and often necessary aspect of successful graduate research.
• The investigations conducted by brain and cognitive science using the advanced neurological mapping methods, such as, Electroencephalogram (EEG), functional Magnetic Resonance Imaging (fMRI) and Positron Emission Tomography (PET) provide a wealth of new information to shed light on the process that helps us learn about creative thinking. Recent studies indicate that the creativity is not confined to right brain regions and is dispersed on both left and right side of the brain and is strongly connected with the emotional centers of the human brain.

14. What is the Difference Between Adaptive Testing and Adaptive Learning? Dec 2011 : https://youtu.be/n5Gh7fri7jc?list=FLceIP70tJjnMfpCUPDGXV7Q

• Dr. Nish Sonwalkar (Sc.D., MIT) provides difference between Adaptive Testing and Adaptive Learning.
• Most often the adaptive learning is confused with the adaptive testing. The adaptive testing is a method in which the difficulty level of questions is adjusted continuously to ascertain the competency level of a learner.
• The questions are posed to the learner, on a given subject matter, with known level of difficulty, say medium level of difficulty and if the student answers questions correctly then the difficulty level is increased. The level of difficulty is increased in each questions posed until the learner starts not answering questions. Then the difficulty level is reduced. By going over several related subject matter areas after sufficient number of questions/answer sessions a score is calculated for the student and then he is put on a percentile basis on the scale by the adaptive testing agency who already have a corpus of normalized data with percentile distribution.
• Most of the testing agencies for aptitude testing use adaptive testing, such as, GRE, GMAT, SAT etc. In adaptive testing based adaptive learning systems the content level of difficulty and explanation is varied based on the question/answer set. However in such systems there is no distinct pedagogy that is used for the variation of content presentation to the user for cognitive opportunity enhancement.
• In true, adaptive learning system, first requirement is to have a pedagogical framework for the presentation of content in three or more learning paths and then there is assessment engine that will provide continuous feedback and rotation of learners through the learning path to reach a desired competency level with desired learning outcome.
• Hence most of the claims made by the adaptive learning systems that are purely based on adaptive testing do not provide sufficient distinction of content in terms of cognitive learning strategies to be termed as adaptive learning systems. We need to dispel the myth that adaptive testing based content presentation systems are adaptive systems and do not match with the learning preference of the individual learners.

15. What is the Difference Between Intelligent Tutors and Adaptive Learning Systems? [Dec 2011] : https://youtu.be/cGwibPdHS8Y?list=FLceIP70tJjnMfpCUPDGXV7Q

• Dr. Nish Sonwalkar (Sc.D., MIT) explains the difference between intelligent tutors and the adaptive learning systems.
• The intelligent tutors were created in early 1980, at the time when artificial intelligence was in fashion. The AI was based on rule based systems where certain rules were created based on the expert knowledge to provide feedback in real time. So the tutors normally were very domain specific.
• For example math tutors where fed with a knowledge representation for the domain of math with expert rules that were fired when a learner was doing a mathematical task. Based on the answers of a given task subsequent scenario were presented. Each scenario steps led to certain rules that provided led to inference by the intelligent tutor to provide certain feedback or practice test.
• By repeated task and feedback intelligent tutors were able to provide reasonable response to each mistake made by the used in their understanding of the mathematical concept. While tutors worked well for a specific domain that was deterministic in nature they failed in areas where there were no correct deterministic answers. Because, there were no if-then-else rules that you could fire in an area like interpretation of poetry.
• The Adaptive Learning Systems on the other had represent knowledge in distinct cognitive pathways such as apprentice, incidental, inductive deductive and discovery -- providing same content in a different contextual framework thereby providing significant cognitive opportunity to learn. Also in the education adaptive learning systems the feedback is given in a different learning pathway to provide another perspective on the same problem.
• Therefore, the an authentic adaptive learning systems is not domain specific and can provide better learning for both scientific disciplines with deterministic answers to domains where the answers are more based interpretation style and there no correct answer.

16. Ten Principles of Personalized Adaptive Education [Dec 2011] : https://youtu.be/zxUW_z9iA2Q?list=FLceIP70tJjnMfpCUPDGXV7Q

• Dr. Nish Sonwalkar (Sc.D., MIT) explains fundamental principles that guide excellence in personalized adaptive education:-

1. One-size-fits-all does not work for online education.

2. Information is not education -- the current web based learning is creating information overload.

3. Learning requires a cognitive process along with multi-media content.

4. Individuals not only learn differently but they also learn different content in different learning strategy.

5. Every individual has a learning strategy based on cognitive development and a learning pace to digest new leaning content.

6. Individualised learning is the only way to reach higher completion rates and faster learning.

7. Learning is four dimensional which includes -- multimedia, cognitive strategies, interactivity and social learning.

8. The only meaningful assessment is one that helps learner improve and reach desired competency.

9. Anyone can reach learning competency with right learning strategy and pace of learning.

10. The best role of instructors is to guide students on how to learn not just what to learn.

17. What is Bloom's Taxonomy and it's relevance to Adaptive Learning? [Feb 2012] : https://youtu.be/4WgA1Zo7ofo?list=FLceIP70tJjnMfpCUPDGXV7Q

• In this video, Dr. Nish Sonwalkar explains Bloom’s taxonomy, its use and need for new taxonomy for adaptive learning systems.
• Benjamin Bloom chaired a committee in 1956 to come up with taxonomy that will categorize the learning objectives for the courses. The important contribution was to include three factors in the learning objective -- cognitive, affective and psychomotor activities to reach a given learning objective. The taxonomy included a set of verbs or an action items that required teachers to design their lessons and instruction to include all three learning modalities -- knowing, feeling and doing.
• There have been several revisions and additions to the Bloom's taxonomy, but it is perhaps one of the most influential taxonomy used widely by the instructional designer and curriculum designer in k-12.
• References: Bloom, B.S. (1956) "The Taxonomy of Educational Objectives: The classification of educational goals, Hand Book 1: Cognitive Domain" Longman, New York. Sonwalkar, N. (2004) "Changing the Interface of Education," Amazon Direct Publishing, Amazon.com

18. What is the difference between Learning Styles and Learning Strategies for Adaptive Learning? [Feb 2012] : https://youtu.be/draZHMIj5OU?list=FLceIP70tJjnMfpCUPDGXV7Q

• Dr. Nish Sonwalkar explains the difference between learning styles and learning strategy, and present argument that for success of adaptive learning we need learning strategies not learning styles.

19. Changing the Interface of Assessment for Courses with Concept Mastery [Feb 2012] : https://youtu.be/_F1VdLvzk2o?list=FLceIP70tJjnMfpCUPDGXV7Q

• The current course assessment depends on few mid-terms and a final paper or exam. This system does not encourage learning but cramming. Dr. Sonwalkar present an alternative model of continuous assessment based on concept mastery where learning is at the center of course delivery

20. Adaptive Mobile Learning (AMOL): A New Model of Integrated Apps [Feb 2012] : https://youtu.be/j4D44lVK6CY?list=FLceIP70tJjnMfpCUPDGXV7Q

• Dr. Nish Sonwalkar points out the surge in the smart phones and the apps that are flooding the market spaces -- such as, App Store, iTunes, App Market. The iPad sales alone reached 40 Million in North America during the year 2011.

21. TOPICS written by Dr. Sonwalker on "Online Education & Pedagogy” (from his website : www.sonwalkar.io)

• Brain-wave Adaptive Learning
• Future of MOOCs: Sanjay Sarma, Kathy Pugh and Nish Sonwalkar MIT Enterprise Forum
• INVASION OF THE MOOC - PART 2 Panel Discussion June 2013
• Adaptive MOOCs: Dr. Nish Sonwalkar and Prof. Anant Agarwal Keynote
• Adaptive and Synaptic Learning and MOOCs: MIT Club of New Hampshire Keynote:
• Brain-based Adaptive Learning: A New Frontier for Liberated Learning :Keynote
• Brain-based Adaptive Learning for Developing Creative Thinking - Keynote

Dr. Nish Sonwalkar’s Speech at the Digital Learning Congress [A Must Watch – 32min. Video] : https://www.youtube.com/watch?v=1ExVkqI1s34