Building Cognitively Informed Simulators Utilizing Multiple, Linked Representations Which Explain Core Concepts in Modern Biology Diana Marie Bajzek, Office of Technology for Education, Carnegie Mellon University, USA
[email protected] James M. Burnette, Department of Biological Sciences, Carnegie Mellon University, USA
[email protected] William E. Brown, Department of Biological Sciences, Carnegie Mellon University, USA
[email protected]
Abstract: The purpose of this paper is to share the process and products of a simulation/tutorial environment under development to be used in the online Modern Biology course for the Open Learning Initiative (OLI), at Carnegie Mellon University, funded by the William and Flora Hewlett Foundation. This project is devoted to developing “cognitively informed”, and openly available, online courses and course materials. While in the early stages of course development, we are focusing on the creation of simulation environments, interactive animations and reference materials, to address key concepts identified by cognitive task analyses within the domain areas. As we move beyond the initial development stages of our simulation environment, we will test this environment before continuing to construct additional simulation tools and storyboard scripts. We want to encourage instructors, and instructional material developers from other institutions to evaluate our environment, provide feedback and contribute new tools to the toolbox.
In the Pursuit of Enhancing Course Content Introduction We are developing simulation environments that facilitate multiple, linked representations of concepts to be used in different learning contexts. They will allow guided inquiry as well as student directed experimentation and data analysis. These environments will be the interactive components of an online Modern Biology course being created as part of the Online Learning Initiative (OLI) project at Carnegie Mellon University (http://www.cmu.edu/oli/). (Smith & Thille 2004) In the teaching of Biology, scientific terms, illustrations and standard 2D representations (graphs and symbols) used in standard practice are what are made available to students in their textbook and classroom lectures. While experts of the domain can easily interpret these terms and representations, novices may struggle to understand their meaning. As a set of visual representations, scientific formats are likely to take a place alongside charts and graphs as representations that students must master to become competent decision makers in a world that is increasingly influenced by science and technology (Edelson et al. 1999). While additional illustrations, animations and instructor explanations can help, for many students, comprehension of these representations is not complete without experimentation and the manipulation of real objects in the lab. Lab experience is not always possible given the enrollment size of the classes, cost, personnel, and space limitations. Many educators and online courses are turning to animations and other multimedia presentations to replace the lab experience. Some of these are guided tours with a minimal amount of student input, while others are exploratory simulations of a laboratory setting. Students find these multimedia tools useful because they can complete them at their own pace, as well as benefit from multiple repeats of the simulation.
Lab vs. Simulations Although lab experience may seem ideal, it may not be the most beneficial for the students. For example, it is not a very controlled environment for learning. Usually one cannot pause a lab experiment to point out what is happening. Experiments, especially biological reactions, often occur in the abstract since the actual reaction is intangible and invisible. Simulations can address these problems. They can be constructed to magnify key situations as well as linking to data, charts and simulated recording instruments. Research shows that students benefit from multiple representations of concepts. Our simulation environment is designed to make it easy for the instructor to link these multiple representations. Simulations provide the opportunity to isolate parameters and explore them directly. They can provide explanations at opportune times, whereas a real experiment often cannot be stopped or the instructor is helping other students. Simulations allow the students to repeat the experiment multiple times, if they wish. Experiments are multiple step processes, often occurring over multiple days, with many opportunities for failure and loss of learning opportunities. Simulations facilitate the compression of time, in order to complete experiments and reduce the opportunities for failure. So, while wet lab experiments are valuable to the students, the use of simulation environments to augment the instruction provides numerous additional values. Problem Getting Appropriate Simulations While simulations can be useful to students, they require much of the educators time to develop and are often short lived: either due to lack of continued interest by the instructor, lack of time to develop, lack of supporting software, or hardware obsolescence. Further, these pieces are often developed on a course-by-course basis usually without instructor coordination or thought to reusability. One solution to this problem is to purchase a set of tools from textbook or software publishers. A major limitation, with even the best of these materials, is that they reflect the ideas and perspectives of the publisher rather than the instructor, and are not easily re-purposed. Thus, an instructor must design his class around a set of objectives that may not meet their criteria or course. This is backwards; the objectives of the local course should dictate the content of interactive multimedia. These materials should allow instructors to collaborate to design common content and tools with varying levels of difficulty for several courses. Designing custom content and interactive tools, as well as a delivery environment that can collect information from students and return feedback and grades, is more development effort than most courses or departments can afford.
Our Solution Environment for Inquiry Based Activity Inquiry, or the pursuit of open questions, is fundamental to the practice of science. Part of teaching Modern Biology must incorporate an appreciation for, and practice of, scientific methods for understanding and learning science. Research in cognitive science supports the importance of activity and authentic contexts for learning, which provide the learner with the scaffolding so that they can learn how to approach acquiring new knowledge. Our simulation/tutorial environment has been designed to encourage effective learning behaviors by follow the principles identified by the research done by Blumenfield et al. (1991). They identified six contributions that technology can make to the learning process: 1) 2) 3) 4) 5) 6)
Enhancing interest and motivation Providing access to information Allowing active, manipulable representations. Structuring the process with tactical and strategic support Diagnosing and correcting errors Managing complexity and aiding production
The Team To create the rich online experience of an OLI course, we’ve assembled a team of educational media and content professionals. At the core of the team are three biologists with many years of experience in teaching biology. They have identified the core concepts Carnegie Mellon students must master to succeed in molecular and cellular biology, as well as difficulties students are experiencing. These faculty members are collaborating to coordinate the materials they develop to prevent gaps in the concepts being presented. The team also includes an educational technology expert with many years of experience in developing and deploying educational technology in the classroom, and a course content developer and scientific liaison. We also have dedicated Flash programming and design support. Through the OLI project we have access to cognitive scientists and design experts to guide the development of the tools. Overview of The Environment We are developing an integrated environment to be used for guided inquiry, practice and self-assessment, open inquiry, context-sensitive feedback, and graded assessment activities using Macromedia Flash®. The environment provides a consistent mechanism to allow written communication between the instructor and student as the instructor guides the student from current concepts to new ones. It contains areas where the student can interact with the linked representations, simulations and other tools (see Fig. 1.) As the instructor pulls back the scaffolding to allow the student more freedom to explore and for assessment, the overall environment will still remain familiar to the student. The support areas of the environment will allow the instructor to provide data resources, capture the students lab journal and graded work and log usage data.
Figure 1: The Environment Shell. One possible organization: 1) Explanatory text, instructions, or questions, 2) optional student text input box, 3) action buttons, 4) simulation, journal, and resources, 5) reaction diagrams, equations, and user inputs 6) charts, graphs, and other data representations.
We are developing a set of learning objects (or tools) that will encode their capabilities in a metadata description and communicate their methods and variables to other tools. We are designing the environment to be "plug and play", such that learning objects can be reused for different purposes or new ones can be built. This will permit an instructor to design simulations that are precisely tailored to the learning objectives of his class, much as a "wet" lab experiment can be modified to meet the same needs.
Once the instructor selects a set of tools, he describes the action or events of the lesson in a series of steps encoded in XML. We envision the XML storyboard to be the most portable aspect of our environment. If an instructor finds a different environment that can duplicate the behaviors described in the XML, then the instructor should be able to use the new environment with little effort. An Example Modern Biology is a one semester overview course of the molecular, cellular, and genetic branches of biology, introducing students to the core concepts. This course presents Modern Biology as an inquiry based science where hypotheses can be made based on observations and tested via experiments and measurements; not just the practice of classifying organisms. In parallel with the initial design of the simulator environment, we did a task analysis of an enzymatic reaction. This analysis resulted in a list of all the concepts and tasks a student needs to master in order to understand enzyme kinetics. We need to isolate and demonstrate four core concepts, namely: equilibrium, energy, rate control and bioselectivity. The first implementation focuses on equilibrium. We have developed several tools for the environment that show the concepts in several linked representations: reaction diagram, numeric data, simulation, and graphs (see Fig. 2). To help students visualize the concept of equilibrium, the simulation represents a highly magnified view of a test tube containing a protein and its ligands. The simulation closely models enzyme kinetics without using detailed mathematical models.
Figure 2: Equilibrium Lesson Demonstrating the Linking of Multiple Representations. As the simulation runs, the number of proteins (red balls) that are in the bound state change with each cycle of the event loop. These numbers are captured and shown to the student as part of the reaction diagram. These numbers are then graphed in two different graphing tools, on a chart recorder that shows the instantaneous number of bound proteins, and in a time-averaged graph. Providing students with all of these representations allows them to link what happens in the test tube with the way that scientists would represent the reaction, i.e., the reaction diagram and the time-averaged graph.
We will initially provide the simulation with the number of input ligands, allowing the student to see the reaction begin in a state of disequilibrium and quickly reach the equilibrium state. The tutorial is a step-by-step explanation of the action and how to interpret the graphs, based on initial inputs provided by the instructor. We then allow the student to restart the system using their own inputs to explore how the activity changes.
After the students complete the tutorial and explore in the instructor directed mode, they will enter a self-assessment mode. In this mode, the student will interact with the simulations, answer questions that allow him to test his new knowledge, and receive immediate feedback. The quantity and quality of the practice will allow him to develop deeper understanding of the material (McAlpine 2004). Feedback can either be in the form of a few sentences in the text area, or it can be step-by-step explanations in the tutorial mode. In the self-assessment mode, the student's answers are not recorded. Once a student feels comfortable with the new concepts, they can enter the graded assessment mode. In this mode, the student will be asked a mixture of multiple-choice and open ended questions, as well as have interactions with the simulations. These responses are made available to the instructor, and grades are recorded in the grade book. The same environment is used in all modes. Once students learn to interact with one environment, they can concentrate on the tasks rather than learning new interfaces. In parallel with development of the Modern Biology tutorials, we are developing sessions for the Biochemistry course. This way, we can develop our tools more broadly from the onset. Unlike the directed tutorials used in Modern Biology, the Biochemistry course will use the environment to conduct more open-ended experiments. For experiments in enzyme kinetics, the student will be provided with a list of beginning points and will need to determine how to proceed. Data and feedback will be provided to the student. The student must choose how to represent and interpret the data to draw conclusions. Data and other decisions will be logged to the Journal for student reference, and to the grade book for grading by the instructor. The storyboards developed for the Modern Biology class, may also be of use in Biochemistry. One of the key aspects of cognitive theory is to provide timely and context sensitive feedback. If a student has problems with specific parts of the kinetics experiments, he can be directed to a simulator loaded with the appropriate storyboard for remedial help. Thus, students will have the opportunity to refresh their understanding of various concepts by exploring them in isolation again. It is also possible that students who excel in Modern Biology will have the opportunity to use the Biochemistry modules, allowing them to develop a richer understanding of the material.
Conclusion From this example you can see that our environment provides one solution to the problem of the limited nature of pre-packaged multimedia tools and virtual labs. The environment provides a space to plug in tools and conversation between the student and instructor. It provides the means to build assessments and log responses as well as other data. Most importantly it allows collaboration in the development and re-use of tools in multiple courses providing continuity of content for the students. As we develop this environment, we are planning user testing of the interface and its effectiveness. The interface will be tested using small focus groups of target students. We also plan to test tutorials using students enrolled in the Spring 2005 Modern Biology class. These students will be asked to complete pre- and post-quizzes on the concepts being presented as well as transfer quizzes assessing whether the student acquired a deep enough understanding to apply the concept to new areas. The quizzes will be developed with help from cognitive scientists and assessment experts who are members of the OLI team. The results of these tests will help to guide future development of the environment and the way in which concepts are presented to the students. The environment is also capable of logging every student "click" to a database separate from the grade book. This data can be analyzed to identify and further explore trends in student use. A key feature of the environment is its abstraction. Other OLI course developers are interested in using the environment in their courses. We want to encourage instructors, and instructional material developers outside of Carnegie Mellon University, to evaluate our environment and provide feedback, and, if applicable, to adopt the environment, use our tools, and contribute new tools to the toolbox.
References Blumenfield, P. C.., Soloway, E., Marx, R., Krajcik, J.S., Guzdial, M., & Palincsar, A. (1991). Motivating projectbased learning: Sustaining the doing, supporting the learning, Educational Psychologist, 26, 369-398. Edelson, D.C., Gordin, D.N., Pea, R.D. (1999). Addressing the Challenges of Inquiry-Based Learning Through Technology and Curriculum Design. The Journal of the Learning Sciences, 8 (3&4), 391-450. McAlpine, L. (2004) Designing learning as well as teaching: A research-based model for instruction that emphasizes learner practice. Active Learning in Higher Education, 5 (2),119-134. Smith, J.M. and Thille, C. (2004). The Open Learning Initiative: Cognitively Informed E-Learning. The Observatory on Borderless Higher Education.
Acknowledgments Professors William Brown, William McClure, and Gordon Rule in the Department of Biological Sciences at Carnegie Mellon University are the instructors guiding development. Ornella Pagliano helped with Flash animations. This project is supported by grants from the Howard Hughes Medical Institute, the William and Flora Hewlett Foundation (Online Learning Initiative) and the Office of Technology for Education at Carnegie Mellon University.
