Large classes offer a major challenge to giving guidance and feedback to students. Online homework assignments with automated feedback offer potential for student practice and guidance. In the study of such homework in Economics and Business Statistics courses, there was an advantage not only for multiple choice items, but but essays which become easier to grade when posted online (no need to deal with handwriting fog!).
Tools for applications discussed in this session included MyEconLab, Respondus, and Aplia in the Moodle LMS. With the homework system, students often also have the advantage of teh e-text, which tends to be cheaper than the print textbook.
Student surveys showed that most felt that they learned more from online homework, and some saw no particular difference with homework online; most felt that it took less time or that there was no difference in the time required to do online homework. The Pearson correlation coefficient did not show a strong correlation of homework grades with the final exam scores. Additional analysis needs to be done to complete the study.
Even though students reported that the homework helped them to learn, they reported that they probably would not do the homework if it were not graded.
Presenter: David Doorn, University of Minnesota Duluth
Showing posts with label online learning. Show all posts
Showing posts with label online learning. Show all posts
Monday, March 16, 2009
Saturday, March 14, 2009
The Power of Course Design
Goodson and Ahn reviewed the threads of design elements that make a variety of support technologies effective for learning, including instructional television, audio, computer applications, and particularly online learning. Russell after a review of over 355 studies about online vs. classroom, concluded that the power was in the design. Recent research suggests the same (Zhao, Let, Yan, & Tan, 2005) where advantages of online seemed due to differences in design, not in technology. Fink's recent work (2007) also shows the power of design in several studies that produced improved learning through a design process that aligns goals with activities and assessments and feedback for "significant learning" outcomes.
In this session, the case study of the design of an aesthetics course was analyzed to show the progression of decisions and the evolving architecture for the course content, the learning activities (including quizzes), and the assessments. The first stage was the question of what constitutes significant learning? The former course design focused on fashion for body types in restrictive stereotypes; the new course design focused on authentic design processes that lead to fashion design (not just choosing fashion), beginning with sources of inspiration and leading to analysis of fashion elements such as line, balance, rhythm, complexity, and color. In this process of deciding on "significant learning," the human dimension was deepened, and a sense of caring was embedded in the images and language structure of the course.
Shifting to meaningful "significant learning" was beginning with the "why" of what we teach. This then triggered decisions about the course goals, leading to the major modules in the course. Quizzes, discussions, and assessments were designed to match each other and required responses from students that often did not have a "yes" or "no" or distinctively correct answer, but required the application of knowledge and principles.
Feedback was staged to allow students to take the quizzes with automated feedback, in the form of correct answers for multiple choice questions, and in the form of "Did you cover...? If not, you may need to..." for more "open" questions.
Discussion questions asked for examples of concepts and reasoning; the process was to allow discussion without response from the instructor until near the end of the week, who would then summarize the main ideas from the discussion. The instructor also would intervene if a concept was not being addressed correctly so that students would not go down a dead end.
In this session, the group reviewed several module structures to follow the design and architecture of the "information and question pages" and they listed and viewed a Camtasia component of instruction, noting the explicit character of the steps and the use of audio to give directions.
Goodson and Ahn returned to the simplicity of the concepts of design, and the power they possess in transforming the learning - first, determining what is significant learning, then aligning all components of the course with this decision.
Results in this case study as compared with the older edition of the course included: significant learning and insights expressed by students in discussions about "the aesthetics of fashion design" rather than "body type," a "world of fashion" rather than restricted stereotypes or parochial fashions, authentic images inclusive of multiple cultures and both male and female gender rather than females only, a larger distribution of higher grades, and no failures.
Presenters: Ludwika A. Goodson, Embry-Riddle Aeronautical University, InSook Ahn, Georgia Southern University
In this session, the case study of the design of an aesthetics course was analyzed to show the progression of decisions and the evolving architecture for the course content, the learning activities (including quizzes), and the assessments. The first stage was the question of what constitutes significant learning? The former course design focused on fashion for body types in restrictive stereotypes; the new course design focused on authentic design processes that lead to fashion design (not just choosing fashion), beginning with sources of inspiration and leading to analysis of fashion elements such as line, balance, rhythm, complexity, and color. In this process of deciding on "significant learning," the human dimension was deepened, and a sense of caring was embedded in the images and language structure of the course.
Shifting to meaningful "significant learning" was beginning with the "why" of what we teach. This then triggered decisions about the course goals, leading to the major modules in the course. Quizzes, discussions, and assessments were designed to match each other and required responses from students that often did not have a "yes" or "no" or distinctively correct answer, but required the application of knowledge and principles.
Feedback was staged to allow students to take the quizzes with automated feedback, in the form of correct answers for multiple choice questions, and in the form of "Did you cover...? If not, you may need to..." for more "open" questions.
Discussion questions asked for examples of concepts and reasoning; the process was to allow discussion without response from the instructor until near the end of the week, who would then summarize the main ideas from the discussion. The instructor also would intervene if a concept was not being addressed correctly so that students would not go down a dead end.
In this session, the group reviewed several module structures to follow the design and architecture of the "information and question pages" and they listed and viewed a Camtasia component of instruction, noting the explicit character of the steps and the use of audio to give directions.
Goodson and Ahn returned to the simplicity of the concepts of design, and the power they possess in transforming the learning - first, determining what is significant learning, then aligning all components of the course with this decision.
Results in this case study as compared with the older edition of the course included: significant learning and insights expressed by students in discussions about "the aesthetics of fashion design" rather than "body type," a "world of fashion" rather than restricted stereotypes or parochial fashions, authentic images inclusive of multiple cultures and both male and female gender rather than females only, a larger distribution of higher grades, and no failures.
Presenters: Ludwika A. Goodson, Embry-Riddle Aeronautical University, InSook Ahn, Georgia Southern University
Friday, March 13, 2009
Online Versus In-class Teaching: Learning Levels Explain Student Performance! AND Are Some Students Better Suited for Online Class...?
I'm reporting on two sessions in this post because they are tightly interwoven and created by the same presenters.
Both sessions began by reviewing the growth rate in online learning (Sloan Report, 2007). In one, we responded to the question "Is online learning for everyone?" Some answers focused on convenience and flexibility (Who is Best Suited for Online Learning? Online Universities Weblog). Some focused on traits commonly cited such as independence, discipline, self-motivation, liking to read and write, ability to stay on task (Is Online Learning for You?). The group agreed that students with these traits would be successful whether learning online or in the classroom.
As to whether there are differences in learning from online vs. onground delivery, both sessions referred to findings in some studies that online is better, in others that classroom is better, and in many that there are no differences (as reported at WCET No Significant Differences Web site). (In this review of findings, there was no analysis offered of whether course design or instructional activities could be the reason for divergent results more than mode of delivery. However, participants in both sessions brought up the question of the alignment with instructional strategies.)
The focus for each session was whether students with different learning styles may perform better online (Index of Learning Styles Questionnaire by Soloman and Felder). To measure student learning performance in this study, the exam had items explicitly aligned with each level of the "old Bloom" taxonomy - 5 items for each level of learning. The exam creators checked reliability of their classifications of items into each of the learning categories.
The course, taught online and onground, had a common syllabus, common final exam, comparable number of students, and students with comparable GPAs. These were some of the differences:
While there seemed to be no differences in online vs. onground learning except in synthesis outcomes, the structure of the assessment design in this study holds promise for sharper analysis of impact on learning outcomes. The data produced some controversial speculation about whether there will be NSDs at all but the synthesis level; discussion in each session pointed out a couple of possible pitfalls in analysis - namely, if the course has not been designed and delivered with synthesis learning activities in the online as well as onground course sections, then it is not valid to conclude that either mode of delivery has produced better results than the other.
The data showed, after controlling for GPA and differences in qualitative majors, that online students did not perform as well on the synthesis items. But the study did not show the reasons.
The design also omitted the "evaluation" level of learning, so performance on that level was not tested.
The paper on this research should be developed in about a month, and I've requested a copy of the complete report from each of the presenters in each session. One of the presenters expressed interest in finding out more about instructional strategies known to work for different types of learning outcomes, about Webb's curriculum and assessment alignment model, the hierarchy of Gagne and Briggs, and re-examination of what is now defined as the highest level of learning in the "revised Bloom's taxonomy."
I think this was a well designed study and could serve as a good model for future exploration.
Presenter: Milind Shrikhande and Richard Felder Georgia State
University
Both sessions began by reviewing the growth rate in online learning (Sloan Report, 2007). In one, we responded to the question "Is online learning for everyone?" Some answers focused on convenience and flexibility (Who is Best Suited for Online Learning? Online Universities Weblog). Some focused on traits commonly cited such as independence, discipline, self-motivation, liking to read and write, ability to stay on task (Is Online Learning for You?). The group agreed that students with these traits would be successful whether learning online or in the classroom.
As to whether there are differences in learning from online vs. onground delivery, both sessions referred to findings in some studies that online is better, in others that classroom is better, and in many that there are no differences (as reported at WCET No Significant Differences Web site). (In this review of findings, there was no analysis offered of whether course design or instructional activities could be the reason for divergent results more than mode of delivery. However, participants in both sessions brought up the question of the alignment with instructional strategies.)
The focus for each session was whether students with different learning styles may perform better online (Index of Learning Styles Questionnaire by Soloman and Felder). To measure student learning performance in this study, the exam had items explicitly aligned with each level of the "old Bloom" taxonomy - 5 items for each level of learning. The exam creators checked reliability of their classifications of items into each of the learning categories.
The course, taught online and onground, had a common syllabus, common final exam, comparable number of students, and students with comparable GPAs. These were some of the differences:
- there were fewer students whose majors were quantitative (e.g., computer science) vs. qualitative fields (e.g., liberal arts) in the online delivery
- there was one instructor for the online course, and multiple instructors for the onground delivery
- the instructional activities and quizzes during the course were idiosyncratic to the preferences of the TA's, thereby making the instruction different in each section of the course
While there seemed to be no differences in online vs. onground learning except in synthesis outcomes, the structure of the assessment design in this study holds promise for sharper analysis of impact on learning outcomes. The data produced some controversial speculation about whether there will be NSDs at all but the synthesis level; discussion in each session pointed out a couple of possible pitfalls in analysis - namely, if the course has not been designed and delivered with synthesis learning activities in the online as well as onground course sections, then it is not valid to conclude that either mode of delivery has produced better results than the other.
The data showed, after controlling for GPA and differences in qualitative majors, that online students did not perform as well on the synthesis items. But the study did not show the reasons.
The design also omitted the "evaluation" level of learning, so performance on that level was not tested.
The paper on this research should be developed in about a month, and I've requested a copy of the complete report from each of the presenters in each session. One of the presenters expressed interest in finding out more about instructional strategies known to work for different types of learning outcomes, about Webb's curriculum and assessment alignment model, the hierarchy of Gagne and Briggs, and re-examination of what is now defined as the highest level of learning in the "revised Bloom's taxonomy."
I think this was a well designed study and could serve as a good model for future exploration.
Presenter: Milind Shrikhande and Richard Felder Georgia State
University
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