Getting Started with Adaptive Learning

This article appeared in the March 2016 issue of Online Classroom.

What is adaptive learning?
Adaptive learning has drawn growing interest in education. The premise makes perfect sense. Instead of giving students of all knowledge and abilities the same content, the student is first assessed on his or her knowledge, then provided the content appropriate to that knowledge. The student does not have to sit through content he or she already knows and receives a customized education.

UCF and Realizeit
We at the University of Central Florida (UCF) recently started experimenting with adaptive learning. After reviewing a number of products, faculty overwhelmingly chose Realizeit from CCKF. The main selling point was that the platform is content agnostic, meaning that it can accept any course material, including text, videos, and graphics. Other products require you to use their content, but this system provides only the infrastructure for supporting your own content.

Faculty also liked the fact that both the content and the assessments are adaptive. The student watches the content and then does the assessment. If the student excels in the assessment, the system will move him or her ahead to more advanced content and more advanced questions. If a student is not doing well in a particular area, the system will recommend that he or she repeat content areas, with the questions decreasing in difficulty.

UCF piloted two courses in fall 2014 using Realizeit: Nursing Pathophysiology and General Psychology. The pathophysiology instructor was intrigued by the case study capabilities of the system. She created three case studies for the fall semester, each with a full description of the particular case, including the age, sex, basic medical history, and current lab information on the patient. Each case study included the same underlying condition like diabetes or poor glucose management, but also included variable information that could modify each case, such as different lab result ranges and various diagnoses. The patient could have high glucose levels but be okay, while low or high levels on other lab results could radically change a diagnosis. This type of scenario means that different students could arrive at different answers concerning each case.

The content in the psychology course consisted of PowerPoint presentations, PDF documents, and some basic content pages. The content was moved into the Realizeit system and tweaked into smaller learning chunks. For instance, the PowerPoint presentation slides were divided into small learning pieces and, using formative assessment, questions related to each section were created or appropriately linked to the content.

Student experience
At the beginning of each module in Realizeit, students complete a “Determine Knowledge” formative assessment where they rate how much they already know about a specific area of content. The system then tests the student’s knowledge based on his or her ranking. If a student does well on the questions, he or she is moved forward so the student doesn’t have to relearn a familiar topic. If a student scores low in an area, he or she is moved back to review the content. Once the system has determined where the student should begin, a learning path is created and he or she may begin on that recommended path. Questions are also included in content areas. Similar to Determine Knowledge, if students are doing well answering questions, the system will move them through the content. If students do poorly, the system sends them back to review a particular section of information.

Instructor role
The instructor role in adaptive learning changes from lecturer to facilitator. The system allows the instructor to quickly identify not only those students who need more assistance, but where they need assistance. For example, when an instructor logs in to the system, Realizeit provides a class update with information about who has not yet started the module, which students are working behind the rest of the section, and how many (and which) students have finished the module. Data is provided on each question as well, such as how many (and which) students answered each question correctly, how many students answered incorrectly, and how much time it took each student to answer a question. This information is especially crucial for large online classes because it allows the instructor to quickly identify and reach out to a student who is struggling.

Content
Instructors are encouraged to put their content into small learning modules, which could be a few paragraphs of text along with a video, an image, or a graphic. They may also add content-related questions to a summative assessment that usually occurs during a weekly quiz, a midterm, or a final exam period.

In this system, a detailed course map is created based on the course objectives, including what the faculty determines to be the prerequisite skills (which may include some remedial-type information) a student will need to be successful in completing the course. Along with the learning module, the instructor creates formative questions related to the content. These formative questions can be marked as easy, medium, or difficult. However, based on the data gathered by the system as students answer questions, the system itself determines the difficulty parameters (how many students answer a question correctly, how long it takes for each student to answer a question, etc.) for each question.

True adaptive learning uses a formative assessment strategy because it provides the system with immediate feedback on how each student is performing. Information is continually gathered by the system on how each student answers the questions to help determine that student’s recommended path (e.g., if a student does poorly on a topic, the system will offer more practice problems on that topic, if available, and if students do well answering the questions, the system will move the student forward in the content). At any point, students are able to revise and/or practice learning bits in order to improve their grades.

Even though there has been a considerable learning curve related to the use of this product, faculty feel that the advantages outweigh the challenges. Plus, course builders have been hired provide the content creation while faculty provide valuable input as the subject matter experts. In addition, open educational resources (OER) such as Openstax College now offer courses such as Introduction to Psychology and College Algebra that have already been developed using the Realizeit platform, which may entice other UCF faculty to use the platform. Based on the availability of OER and overall positive feedback from instructors and students, we plan to continue to work with faculty to create courses on this platform in the foreseeable future.

Kathleen Bastedo is an instructional designer at the University of Central Florida.

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This article appeared in the March 2016 issue of Online Classroom. What is adaptive learning? Adaptive learning has drawn growing interest in education. The premise makes perfect sense. Instead of giving students of all knowledge and abilities the same content, the student is first assessed on his or her knowledge, then provided the content appropriate to that knowledge. The student does not have to sit through content he or she already knows and receives a customized education. UCF and Realizeit We at the University of Central Florida (UCF) recently started experimenting with adaptive learning. After reviewing a number of products, faculty overwhelmingly chose Realizeit from CCKF. The main selling point was that the platform is content agnostic, meaning that it can accept any course material, including text, videos, and graphics. Other products require you to use their content, but this system provides only the infrastructure for supporting your own content. Faculty also liked the fact that both the content and the assessments are adaptive. The student watches the content and then does the assessment. If the student excels in the assessment, the system will move him or her ahead to more advanced content and more advanced questions. If a student is not doing well in a particular area, the system will recommend that he or she repeat content areas, with the questions decreasing in difficulty. UCF piloted two courses in fall 2014 using Realizeit: Nursing Pathophysiology and General Psychology. The pathophysiology instructor was intrigued by the case study capabilities of the system. She created three case studies for the fall semester, each with a full description of the particular case, including the age, sex, basic medical history, and current lab information on the patient. Each case study included the same underlying condition like diabetes or poor glucose management, but also included variable information that could modify each case, such as different lab result ranges and various diagnoses. The patient could have high glucose levels but be okay, while low or high levels on other lab results could radically change a diagnosis. This type of scenario means that different students could arrive at different answers concerning each case. The content in the psychology course consisted of PowerPoint presentations, PDF documents, and some basic content pages. The content was moved into the Realizeit system and tweaked into smaller learning chunks. For instance, the PowerPoint presentation slides were divided into small learning pieces and, using formative assessment, questions related to each section were created or appropriately linked to the content. Student experience At the beginning of each module in Realizeit, students complete a “Determine Knowledge” formative assessment where they rate how much they already know about a specific area of content. The system then tests the student's knowledge based on his or her ranking. If a student does well on the questions, he or she is moved forward so the student doesn't have to relearn a familiar topic. If a student scores low in an area, he or she is moved back to review the content. Once the system has determined where the student should begin, a learning path is created and he or she may begin on that recommended path. Questions are also included in content areas. Similar to Determine Knowledge, if students are doing well answering questions, the system will move them through the content. If students do poorly, the system sends them back to review a particular section of information. Instructor role The instructor role in adaptive learning changes from lecturer to facilitator. The system allows the instructor to quickly identify not only those students who need more assistance, but where they need assistance. For example, when an instructor logs in to the system, Realizeit provides a class update with information about who has not yet started the module, which students are working behind the rest of the section, and how many (and which) students have finished the module. Data is provided on each question as well, such as how many (and which) students answered each question correctly, how many students answered incorrectly, and how much time it took each student to answer a question. This information is especially crucial for large online classes because it allows the instructor to quickly identify and reach out to a student who is struggling. Content Instructors are encouraged to put their content into small learning modules, which could be a few paragraphs of text along with a video, an image, or a graphic. They may also add content-related questions to a summative assessment that usually occurs during a weekly quiz, a midterm, or a final exam period. In this system, a detailed course map is created based on the course objectives, including what the faculty determines to be the prerequisite skills (which may include some remedial-type information) a student will need to be successful in completing the course. Along with the learning module, the instructor creates formative questions related to the content. These formative questions can be marked as easy, medium, or difficult. However, based on the data gathered by the system as students answer questions, the system itself determines the difficulty parameters (how many students answer a question correctly, how long it takes for each student to answer a question, etc.) for each question. True adaptive learning uses a formative assessment strategy because it provides the system with immediate feedback on how each student is performing. Information is continually gathered by the system on how each student answers the questions to help determine that student's recommended path (e.g., if a student does poorly on a topic, the system will offer more practice problems on that topic, if available, and if students do well answering the questions, the system will move the student forward in the content). At any point, students are able to revise and/or practice learning bits in order to improve their grades. Even though there has been a considerable learning curve related to the use of this product, faculty feel that the advantages outweigh the challenges. Plus, course builders have been hired provide the content creation while faculty provide valuable input as the subject matter experts. In addition, open educational resources (OER) such as Openstax College now offer courses such as Introduction to Psychology and College Algebra that have already been developed using the Realizeit platform, which may entice other UCF faculty to use the platform. Based on the availability of OER and overall positive feedback from instructors and students, we plan to continue to work with faculty to create courses on this platform in the foreseeable future. Kathleen Bastedo is an instructional designer at the University of Central Florida.