Since the 2014 high-profile meta-analysis of undergraduate STEM courses, active learning has become a standard in higher education pedagogy. One way to provide active learning is through the flipped classroom. However, finding suitable pre-class learning activities to improve student preparation and the subsequent classroom environment, including student engagement, can present a challenge in the flipped modality. To address this challenge, adaptive learning lessons were developed for pre-class learning for a course in Numerical Methods. The lessons would then be used as part of a study to determine their cognitive and affective impacts. Before the study could be started, it involved constructing well-thought-out adaptive lessons. This paper discusses developing, refining, and revising the adaptive learning platform (ALP) lessons for pre-class learning in a Numerical Methods flipped course.
In a prior pilot study at a large public southeastern university, the first author had developed ALP lessons for the pre-class learning for four (Nonlinear Equations, Matrix Algebra, Regression, Integration) of the eight topics covered in a Numerical Methods course. In the current follow-on study, the first author and two other instructors who teach Numerical Methods, one from a large southwestern urban university and another from an HBCU, collaborated on developing the adaptive lessons for the whole course.
The work began in Fall 2020 by enumerating the various chapters and breaking each one into individual lessons. Each lesson would include five sections (introduction, learning objectives, video lectures, textbook content, assessment). The three instructors met semi-monthly to discuss the content that would form each lesson. The main discussion of the meetings centered on what a student would be expected to learn before coming to class, choosing appropriate content, agreeing on prerequisites, and choosing and making new assessment questions. Lessons were then created by the first author and his student team using a commercially available platform called RealizeIT. The content was tested by learning assistants and instructors. It is important to note that significant, if not all, parts of the content, such as videos and textbook material, were available through previously done work. The new adaptive lessons and the revised existing ones were completed in December 2020.
The adaptive lessons were tested for implementation in Spring 2021 at the first author's university and made 15% of the students' grade calculation. Questions asked by students during office hours, on the LMS discussion board, and via emails while doing the lessons were used to update content, clarify questions, and revise hints offered by the platform. For example, all videos in the ALP lessons were updated to HD quality based on student feedback. In addition, comments from the end-of-semester surveys conducted by an independent assessment analyst were collated to revise the adaptive lessons further. Examples include changing the textbook content format from an embedded PDF file to HTML to improve quality and meet web accessibility standards.
The paper walks the reader through the content of a typical lesson. It also shows the type of data collected by the adaptive learning platform via three examples of student interactions with a single lesson.
more »
« less
Development, Implementation, Refining and Revising of Adaptive Platform Lessons for an Engineering Course
Since the 2014 high-profile meta-analysis of undergraduate STEM courses, active learning has become a standard in higher education pedagogy. One way to provide active learning is through the flipped classroom. However, finding suitable pre-class learning activities to improve student preparation and the subsequent classroom environment, including student engagement, can present a challenge in the flipped modality. To address this challenge, adaptive learning lessons were developed for pre-class learning for a course in Numerical Methods. The lessons would then be used as part of a study to determine their cognitive and affective impacts. Before the study could be started, it involved constructing well-thought-out adaptive lessons. This paper discusses developing, refining, and revising the adaptive learning platform (ALP) lessons for pre-class learning in a Numerical Methods flipped course.
In a prior pilot study at a large public southeastern university, the first author had developed ALP lessons for the pre-class learning for four (Nonlinear Equations, Matrix Algebra, Regression, Integration) of the eight topics covered in a Numerical Methods course. In the current follow-on study, the first author and two other instructors who teach Numerical Methods, one from a large southwestern urban university and another from an HBCU, collaborated on developing the adaptive lessons for the whole course.
The work began in Fall 2020 by enumerating the various chapters and breaking each one into individual lessons. Each lesson would include five sections (introduction, learning objectives, video lectures, textbook content, assessment). The three instructors met semi-monthly to discuss the content that would form each lesson. The main discussion of the meetings centered on what a student would be expected to learn before coming to class, choosing appropriate content, agreeing on prerequisites, and choosing and making new assessment questions. Lessons were then created by the first author and his student team using a commercially available platform called RealizeIT. The content was tested by learning assistants and instructors. It is important to note that significant, if not all, parts of the content, such as videos and textbook material, were available through previously done work. The new adaptive lessons and the revised existing ones were completed in December 2020.
The adaptive lessons were tested for implementation in Spring 2021 at the first author's university and made 15% of the students' grade calculation. Questions asked by students during office hours, on the LMS discussion board, and via emails while doing the lessons were used to update content, clarify questions, and revise hints offered by the platform. For example, all videos in the ALP lessons were updated to HD quality based on student feedback. In addition, comments from the end-of-semester surveys conducted by an independent assessment analyst were collated to revise the adaptive lessons further. Examples include changing the textbook content format from an embedded PDF file to HTML to improve quality and meet web accessibility standards.
The paper walks the reader through the content of a typical lesson. It also shows the type of data collected by the adaptive learning platform via three examples of student interactions with a single lesson.
more »
« less
- Award ID(s):
- 2013271
- NSF-PAR ID:
- 10404649
- Date Published:
- Journal Name:
- Proceedings of ASEE Annual Conference and Exposition
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
more » « less
Abstract Preclass learning, an obstacle in the success of a flipped classroom, is addressed via placing lessons on an online adaptive platform. The lessons combine the power of video lectures, textbook content, simulations, and assessments while using personalized paths for each student. This article describes the development of the adaptive lessons for a course in Numerical Methods, and the interpretation of the analytic data collected via the adaptive lesson platform and student focus groups over a two‐semester period with 146 students. Analytical data includes student metrics, such as the lesson scores and the time spent and lesson metrics, such as the percentage of students who completed the lesson and the percentage of possible adaptive paths used by students. The focus groups were conducted for two different demographic groups—students who are “white males” (comprise the majority of students in public engineering schools in the USA) and “other than white males”—to compare their perspectives on adaptive learning. Students in the focus group of the “other than white male” pupils demonstrated more favorable and positive perspectives towards the adaptive learning compared with the “white males”, although both groups identified benefits with the adaptive platform. Final examination scores were found to be correlated with the raw score of the adaptive lessons.
-
more » « less
Abstract As use of adaptive learning technology in STEM courses gains traction, studies evaluating its impacts are important to undertake. Adaptive e‐learning platforms provide personalized, flexible learning via monitoring of student progress and performance and subsequent provision of an individualized learning path containing various resources. In this study, adaptive technology was utilized in blended and flipped versions of a numerical methods course. A particular challenge with flipped instruction is preclass preparation, in which videos with the same instruction for all students are often assigned. Therefore, to diversify preclass learning, the instructor developed adaptive lessons via an NSF grant and rigorously assessed outcomes in this flipped class with adaptive learning. In addition, to fully evaluate the lessons and respond to calls from the literature, the lessons were implemented and evaluated in a blended version of the course, which was lecture‐based with available online resources. Data from previous semesters of flipped and blended instruction (without adaptive learning were available), enabling a comparison of four instructional methods. The comparisons consisted of direct assessment (i.e., exam questions) and affective assessment via a survey (i.e., perceptions of the classroom environment). An analysis was performed for students collectively and for underrepresented minority students in engineering. Focus groups enabled a comparison of student perspectives of using adaptive technology in blended versus flipped classrooms as well as by demographic. Upon combining these outcomes, including a notable Cohen's
d = 0.34 for open‐ended‐response performance, the flipped classroom with adaptive learning may be the best method for this STEM course. -
Motivation: This is a complete paper. There was a sudden shift from traditional learning to online learning in Spring 2020 with the outbreak of COVID-19. Although online learning is not a new topic of discussion, universities, faculty, and students were not prepared for this sudden change in learning. According to a recent article in ‘The Chronicle of Higher Education, “even under the best of circumstances, virtual learning requires a different, carefully crafted approach to engagement”. The Design Thinking course under study is a required freshmen level course offered in a Mid-western University. The Design Thinking course is offered in a flipped format where all the content to be learned is given to students beforehand and the in-class session is used for active discussions and hands-on learning related to the content provided at the small group level. The final learning objective of the course is a group project where student groups are expected to come up with functional prototypes to solve a real-world problem following the Design Thinking process. There were eighteen sections of the Design Thinking course offered in Spring 2020, and with the outbreak of COVID-19, a few instructors decided to offer synchronous online classes (where instructors were present online during class time and provided orientation and guidance just like a normal class) and a few others decided to offer asynchronous online classes (where orientation from the instructor was delivered asynchronous and the instructor was online during officially scheduled class time but interactions were more like office hours). Students were required to be present synchronously at the team level during the class time in a synchronous online class. In an asynchronous online class, students could be synchronous at the team level to complete their assignment any time prior to the deadline such that they could work during class time but they were not required to work at that time. Through this complete paper, we are trying to understand student learning, social presence and learner satisfaction with respect to different modes of instruction in a freshmen level Design Thinking course. Background: According to literature, synchronous online learning has advantages such as interaction, a classroom environment, and better course quality whereas asynchronous online learning has advantages such as self-controlled and self-directed learning. The disadvantages of synchronous online learning include the learning process, technology issues, and distraction. Social isolation, lack of interaction, and technology issue are a few disadvantages related to asynchronous online learning. Problem Being Addressed: There is a limited literature base investigating different modes of online instruction in a Design Thinking course. Through this paper, we are trying to understand and share the effectiveness of synchronous and asynchronous modes of instruction in an online Flipped Design Thinking Course. The results of the paper could also help in this time of pandemic by shedding light on the more effective way to teach highly active group-based classrooms for better student learning, social presence, and learner satisfaction. Method/Assessment: An end of semester survey was monitored in Spring 2020 to understand student experiences in synchronous and asynchronous Design Thinking course sections. The survey was sent to 720 students enrolled in the course in Spring 2020 and 324 students responded to the survey. Learning was measured using the survey instrument developed by Walker (2003) and the social presence and learner satisfaction was measured by the survey modified by Richardson and Swan (2003). Likert scale was used to measure survey responses. Anticipated Results: Data would be analyzed and the paper would be completed by draft paper submission. As the course under study is a flipped and active course with a significant component of group work, the anticipated results after analysis could be that one mode of instruction has higher student learning, social presence, and learner satisfaction compared to the other.more » « less
-
The emphasis on conceptual learning and the development of adaptive instructional design are both emerging areas in science and engineering education. Instructors are writing their own conceptual questions to promote active learning during class and utilizing pools of these questions in assessments. For adaptive assessment strategies, these questions need to be rated based on difficulty level (DL). Historically DL has been determined from the performance of a suitable number of students. The research study reported here investigates whether instructors can save time by predicting DL of newly made conceptual questions without the need for student data. In this paper, we report on the development of one component in an adaptive learning module for materials science – specifically on the topic of crystallography. The summative assessment element consists of five DL scales and 15 conceptual questions This adaptive assessment directs students based on their previous performances and the DL of the questions. Our five expert participants are faculty members who have taught the introductory Materials Science course multiple times. They provided predictions for how many students would answer each question correctly during a two-step process. First, predictions were made individually without an answer key. Second, experts had the opportunity to revise their predictions after being provided an answer key in a group discussion. We compared expert predictions with actual student performance using results from over 400 students spanning multiple courses and terms. We found no clear correlation between expert predictions of the DL and the measured DL from students. Some evidence shows that discussion during the second step made expert predictions closer to student performance. We suggest that, in determining the DL for conceptual questions, using predictions of the DL by experts who have taught the course is not a valid route. The findings in this paper can be applied to assessments in both in-person, hybrid, and online settings and is applicable to subject matter beyond materials science.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- The DOI is not currently available.
