Providing Multi-Level Assistance to Students in Online Learning Environments
Usage statistics in online learning environments have shown that students work at all hours. To provide on-demand assistance to students, these systems frequently offer hints, feedback, solutions, videos, eBooks, and example problems. This paper discusses WebAssign’s Deep Help framework, a new, multi-level, tutorial-based assistance designed using principles from the Zone of Proximal Development, Knowledge Space Theory, and Cognitive Load Theory. It also highlights the Deep Help framework in action in the classroom and the results from several class test experiences.
Unlike analog homework, students can access online learning environments at any hour of the day and analytics are available to track student usage patterns. As shown in Figure 1, student usage peaks in the evening, when instructors tend to be unavailable.
Online learning environments often incorporate various tools to provide real-time assistance to the student, including hints, feedback, solutions, videos, eBooks, and access to example problems. Students in introductory-level courses frequently come from a diverse set of education backgrounds and consequently require different types and levels of assistance.
Zone of Proximal Development
Vygotsky’s Zone of Proximal Development concept describes the range of abilities that a learner cannot perform independently, but can perform with assistance. The Zone of Proximal Development, represented by the blue center area in Figure 2, is the gap between tasks a learner can do without help and what the learner cannot do, even with assistance.
The role of a teacher is to provide guidance and assistance so that the learner can accomplish tasks in the center section. Teachers can use online learning systems as an extension of their role to provide additional assistance when they are not available. Organizing tasks into each of these segments is further discussed in the Knowledge Space Theory.
Knowledge Space Theory
Knowledge Space Theory considers the dependent relationship between subsets of knowledge. For instance, the concept of the balanced equation for a reaction is a necessary prerequisite for the concept of stoichiometry. This relationship is also why it is rare to assess student understanding of stoichiometry with a problem involving a 1:1 ratio, since that could be solved without meeting the prerequisites.
For instance, in Figure 3a, an understanding of B requires a prerequisite understanding of A. Similarly, D depends on B and C, indicating that to understand D, a learner must already comprehend A, B, and C. Thus a knowledge state of ACE, FACE, or CAB would be possible, but FEB or DEC would not.
Applying the Zone of Proximal Development to a Knowledge Space diagram requires that the three regions be aligned in ways permissible by the dependencies in the diagram. A hypothetical example of this is illustrated in Figure 3b, with a learner able to accomplish A, B, C, E, and F without assistance, D and G with assistance, but unable to perform H. The dependencies make clear that if, for instance, F required assistance, then G would require assistance as well.
Cognitive Load Theory
The major idea behind Cognitive Load Theory is the assumption of a finite cognitive load capacity in a learner. This capacity is spread among intrinsic, extraneous, and germane aspects of the activity being performed. Intrinsic cognitive load comes from the difficulty and complexity of the concept. Extraneous cognitive load relates to the means through which a concept is presented and germane load addresses the construction of schemas. This theory indicates that in order for the student to use the majority of his or her cognitive abilities for learning, it’s important to avoid extraneous tasks and distractions.
Deep Help Framework
The Deep Help framework was designed to provide stepped tutorials for prerequisite information. Students can dive deeper into the provided extra support as needed, until they fully understand all elements required to perform the original problem. The instructor has full control over student access to tutorials and can configure Deep Help to always be available or available only after a specified number of answer submissions. While many interactive tutorials and other help tools are associated at the question level in a student’s assignment, the Deep Help system is associated with individual steps in a tutorial (Figure 4).
Based on the Cognitive Load Theory “just in time” paradigm, Deep Help makes specific tutorials easy to find while the student is learning and limits decision options so that less cognitive load is expended. This is accomplished by limiting the number of tutorials the learner has available to choose from, and each step of the tutorial (highlighted in green) only has one or two options. The multi-step approach used in the tutorial helps the student see which step they are having difficulty with.
From the perspective of Knowledge Space Theory and Zone of Proximal Development, we presume that instructors would assign questions that their students are able to do with assistance, however, we recognize that there are cases where this is not practical, such as before-class assignments or when students have missed class due to illness or other reasons. To use the example shown in Figure 3, the Deep Help system lets a student revisit activities they can accomplish with the assistance of the system (red), which can expand their capabilities to tackle the original question. It is important to note that students would not usually access a large portion of the Deep Help available for a given question, but would dive as deep as needed in an area in which they are having trouble. For students who need extensive help, the tutorial offers a step-by-step breakdown of the problem.
An initial class test took place during the spring semester in 2013 at Tallahassee Community College (TCC) in Florida. TCC has a very diverse student population of more than 13,000 students, with 1,000 enrolled in the General Chemistry course each year. After using the Deep Help system for a semester with a typical set of students, Dr. Joi Walker reported positive feedback, explaining that “we were working on the review problems for Chemistry II and there were lots of questions, because some students wait a few semesters between Chemistry I and II. The tutorials were perfect for these students.”
In fact, when an assignment was accidentally scheduled before the material was covered in class, students were still able to complete the homework assignment using the tutorials in the Deep Help system. This supports the idea that the Deep Help system enables students to accomplish more than they would on their own – as would be expected from the Zone of Proximal Development. One student from this class reflected that “the tutorials helped me out a lot; I wish I would have spent more time doing them so I would have done better on some of my quizzes.”
A second class test was conducted in the summer of 2013 during a first-semester, general chemistry course at a large, state-supported university in the southern United States. The 300 students enrolled in the class were exposed to WebAssign General Chemistry content and the Deep Help framework as part of regular homework assignments related to the classroom lectures. After course completion they were invited to take part in surveys about the question content and Deep Help system.
In this class test, 96% of students indicated that the tutorials in the Deep Help system were helpful or very helpful. 86% of these students also agreed with the statement “I feel that the homework assignments with tutorials will help me learn.”
By applying these learning theories in the design of the Deep Help system, instructors are able to offer additional support to students through the use of an online instructional system that assists students in identifying where they are having trouble, provides multi-level assistance in those areas, and is always available.