Helping On-Line Learners Construct Mental Models of Physical Systems
D. Sammons, Idaho State
University, College of Education
E.S. Lohse, Idaho State University, Department of Anthropology
On-line learning possibilities continue to expand as computer technology advances. When we made our first effort at creating a digital component to an archaeological laboratory course, the result was a stand-alone CD-ROM: Digital Stones (Lohse & Sammons 1998, 2002). Digital Stones taught students concepts they would need to analyze archaeological stone artifacts and to recognize important attributes in macroscopic and microscopic view; it also provided a simulation of encoding those attributes into a database. A primary impetus in the creation of Digital Stones was the lack of laboratory equipment (especially microscopes), as well as of specimens on which the attributes were clear and consistent. Therefore, the original Digital Stones focused on concept teaching and presented those concepts in the same order in which a student analyst would encounter them on an encoding form.
A second iteration of Digital Stones took advantage of technological advances in on-line learning (Lohse, Sammons & Schlader, 2001). The contents of the original CD-ROM were revised and upgraded to be presented in HTML format through WebCT. In this version, Digital Stones provided the content for an entire on-line course and supplemented new instructional goals: namely, the learner would be able to identify and analyze attributes of stone tools through the manufacture, use and analysis of their own specimens. Digital Stones became wedded to a sequence of on-line lessons that included stated objectives, procedures, products, and uploads of digital images and databases with which students recorded their work. Built in WebCT, this course also included assessment components such as objective quizzes and essays.
We are now entering a third edition of the archaeological stone tool analysis course. It continues to be based on the material originally created in Digital Stones and to be offered on-line, but its instructional objectives, content, research basis, and pedagogical approach are new. Our explicit intent is to help our on-line learners construct mental models that integrate the concepts and physical systems involved in making and analyzing stone tools.
The stone tool analysis course is offered at both the undergraduate and graduate levels. Because it is a self-paced, on-line offering, the content is very intensive. The course covers in one semester what a face-to-face laboratory analysis program might cover in two years. Upon completion of the course, students have sufficient background to work as analysts for archaeological projects. The course content provides concept knowledge about stone tool manufacture and use, as well as concept knowledge about analysis and analytical systems. The course also provides application and practice in making and using stone tools, analyzing artifacts, classification, and data construction. Students emerge from the class with more than specific concepts and procedurals; they also have developed extensive mental models that combine concepts and actions integral to stone tool analysis.
“Mental models” are cognitive representations of the learner’s knowledge; their components and structure mirror the components and structure of the system or object they represent (Johnson-Laird, 2004). Some researchers (e.g., Canas, et al., 2003) indicate that a key element of a mental model is the combination of characteristics from the environment with information in long term memory. Although the mental model may be incomplete or even inaccurate, it is the means by which a learner interacts with a physical system, especially in the absence of detailed procedures or necessary information (Canas, et al., 2003). It is crucial that the mental models of the learner (the novice) reflect the mental models of the instructor (the expert); indeed, that is one criterion for determining whether learning has actually occurred. The instructional design must support building the mental model of the learner by providing multiple interfaces (textual, graphic, tactile) through which the concepts of the model may be encoded.
In the analysis of stone tools, the physical system is the manipulation of both raw stone material to create a useful, purposive object. In this case, the learner must combine conceptual knowledge (“information in long term memory”) with hands-on practice in the making of stone tools (“characteristics of the environment”). The learner’s mental model reflects the interaction of these two domains. At first, the two domains represent two different mental models – Concepts and Actions. Concepts are semantic knowledge of characteristics, definitions, and identification; Actions are episodic, procedural knowledge of the stone and how it breaks. As the learner moves beyond the novice level, Concepts and Actions combine into a single mental model.
The analysis of stone tools is a unique study area in that the novice creates a mental model, the expert has a mental model, and both are trying to establish at some level a tie with the mental models of the original makers of stone tools, usually prehistoric peoples far removed in time and space. The mental model of the novice and the expert can be represented by concept maps (cf. Trochim, 1989). A working assumption in archaeology is that the re-occurring stylistic and functional attributes of stone tools reflect the mental models of the original makers and that these too can be graphically illustrated in a concept map (Lohse, 2002). Trochim (1989) argues that concept maps can be both valid and reliable and are useful in pattern matching exercise.
The problem for the on-line laboratory analysis class is to provide learners with knowledge, skills, and opportunities to develop their mental maps about the physical system of stone tool manufacture. These maps may model the trajectory of stone tool manufacture (from raw material to partially reduced core to finished point or knife); they may model the characteristics that separate evidence of manufacture from evidence of use; and they may model the analytical system itself.
The resources for learners include an on-line environment in which concepts are introduced, defined, and illustrated. In the past, concept illustrations were static, but innovations in computer technology have made dynamic, virtual depictions a reality. In a sense, advances in computer technology allow us to insinuate Actions into an instructional context that was previously Concepts.
The goals of the course can be roughly characterized as either Concepts or Actions, although obviously concepts are needed to successfully perform actions and actions represent the successful application of concepts. Learners are assessed on the following concepts and actions through a series of hands-on exercises in which stone tools are manufactured, used, characterized, their characteristics encoded, and the resultant data analyzed. Conceptual models that organize the course include stone tool manufacturing, stone tool use, technological analysis, functional analysis, image processing and analysis, models and lithic analysis, and the application of cognitive models in the interpretation of the analysis. (“Technological” here does not refer to computer technology, but to the technology of stone tools.)
The instructional goals of the on-line laboratory analysis class have similarly changed, from the static (and rote) definition and application of concepts to a dynamic model of the relationship between concepts. In the third version of the on-line analysis class, the instructional goals have become more complex and more dynamic. The goals are to reinforce the relationship between Concepts and Actions and to further the students’ understanding of Actions, especially the human/stone interface and the stone/stone sequence of reduction.
Virtual reality (VR) applications have been used with great success in archaeology. VR has allowed the virtual illustration of archaeological materials in three dimensions so that researchers can view and manipulate specimens at a distance, either through a browser or from a CD/DVD (e.g., Pringle & Moulding, 1997). Examination of specimens that are attached to large databases is also possible (Pringle, 2001), even for the general public. In his extensive work on the use of VR for presentation of archaeological information, Pringle (2000) examines many applications of VR for archaeological imaging, analysis and survey, prototype modeling, and evaluation, but does not mention the possibility of using VR for teaching. In this course, we have developed VR systems to help the on-line student formulate the mental models of Concepts and Actions necessary for successful analysis, interpretation, and publication.
The student stone tool analyst is required to:
(1) obtain knowledge of the field (published literature and concepts)
(2) develop explicit operational knowledge of how stones are flaked and resultant tools used
(3) understand and employ models for analysis and publishing of results
This course mirrors teaching of any concrete skill set in a task requiring application of abstract knowledge to completion of a physical task. Our paper describes success in using an online virtual environment to accelerate student learning of how to flake and use stone tools: a complex skill set involving accelerated development of significant autonomic responses within the constraints of effective application of variable mental models or schema. Goals, discrete tasks, and shifting solution frameworks are all employed by the knappers as variable stones and variable personal skill sets dictate shifting solution frameworks. Goals are consistent, and the fracture properties of stones are predictable. Successful knapping will reside in the skill range defined as novice to expert knapper. The novice is limited by having restricted schema and a more limited skill set. The expert will move adroitly from goal to goal, surmounting problem areas, in an autonomic, non-counscious environment largely based on a sound experential knowledge base.
Example:
Sequential Removal of Flakes from A Prepared Core
We developed intensive, empirically accurate models of stone tool reduction and used in Flash and SpinPhoto as learning modules for our DigitalStones class website. In the example described here, we used Flash to create models of flakes being driven from a core. SpinPhoto was used to simulate the knapper rotating the core to predict where the next flake would be sequential removed. The practical goal was to present students with a clear action model based on extensive research that would accelerate and guide their expertise in removal of flakes from a core to create stone tools.
The exercise (1) reflects extant scholarly literature on the subject; (2) presents clear operational knowledge, and (3) lays the foundation needed to make and use stone tools as part of analytical exercises required in the DigitalStones course.
Use of the virtual online environment accelerates analysts’ learning by providing a compelling visceral experience, including sound and perspective rotations. It also constrains failures within idealized models. The learner has maximal control over the virtual exercises through an attractive, intuitive interface. A detailed database sits behind the interface and movies, providing significant control over depth of immersion. Learners can readily repeat scripted ideational sequences without recourse to beginning the exercise over again and again as would be the case in a real world experience.
We have found the learning experience to be immersive for students. Their skill levels are dramatically augmented by being able to observe goal-action sequences in an ideal environment where they have maximal control over speed and perspective. This is a much clearer situation for the novice than observing the skilled hands of the expert fly over multiple goal-action sequences as is the case in films of actions or in real life performances. In real time, the expert ignores many discrete decision steps and employs complex skill sets at high speed to perform myriad actions, largely without conscious thought. The observor-learner finds it difficult if not impossible to see what is happening at each juncture, and in fact, many times discrete steps in the reduction sequence are obscured by the novices’ positions relative to the physical actions performed or by the expert knappers’ body in performing these physical actions. The virtual online environment eliminates problems of perspective and visibility and instead makes visible all necessary steps and products, with one sequential goal-action leading to the next. The learner benefits by having a clear mental model of what is required to reduce stone to make tools and benefits from having immediate positive feedback that would be missing or hard won in the real world apprentice role of novice to expert.
The DigitalStones course is an interesting study because it combines on-line delivery of course materials supplemented with a highly interactive user interfaces and virtual reality constructions, with required hands-on exercises and weekly face-to-face or online assessments of student progress. Students have immersive experiences, hands-on reinforcement, and continual assessment loops (cf. Marchese 2003; Hake 1998). The context of the course is situated learning, wherein we are attempting to transform students into competent archaeological analysts in a highly compressed period of training. This echoes admonishments by Brown, Collins and Deguid (1989) that the most important knowledge to performance is tacit, and that this knowledge resides within and helps define the relevant community of practice. We are training students to join their archaeological community of lithic specialists, and we are consciously ramping up their experiential base utilizing a combination of situated, virtual and hands-on training to intensify their experience and accelerate their competence in the workplace. We have made every effort to provide our students with "cognitive apprenticeships" that enculturate them in authentic practices through immersive activities and collegial interactions that promulgate learning in the domain by enabling them to acquire, develop and use effective cognitive tools while performing authentic activities (cf. what Marton and Saljo (1976) called "deep learning").
We have employed Csikszentmihalyi"s (1997) emphasis on finding flow in the learning experience. Flow occurs when there is a clear set of learning goals that require appropriate responses, with immediate feedback, and there is the strong conditional requirement that the learners' skills are fully involved in overcoming set challenges. This admonishment is also presented in the TIMSS report demanding efforts at pedagogical flow based on (1) focusing on powerful, central ideas and capacities; (2) pursuing greater depth, so content is meaningful, organized and linked to students' ideas, all prompting student insight and intuition rather than rote performance; and (3) providing rigorous, powerful and meaningful content-produced learning that is lasting and applied.
References:
Brown, J.S., A. Collins and P. Duguid (1989). Situated Cognition and the Culture of Learning. Educational Researcher, 18, no. 1, 32-42.
Canas, J.J., Salmeron, L. Antoli, A., Fajardo, I, Chisalita, C. & Escudero, J.T. (2003). Differential roles for visuospatial and verbal working memory in the construction of mental models of physical systems. International Journal of Cognitive Technology, 8, 45-53. Retrieved December 19, 2004 from http://www.ugr.es/~ergocogn/articulos/mental.pdf .
Csikszentmihalyi, M. (1997). Finding Flow: The psychology of Engagement with Everyday Life. New York: Basic Books.
Hake, R.R. (1998). Interactive-engagement vs. traditional methods: A six thousand-student survey of mechanics test data for introductory physics courses. American Journal of Physics, 66, 64-74.
Johnson-Laird, R. (2004). MITECS: Mental models. Discussions in Human Centered Computing. Retrieved December 19, 2004 from http://paulos.net/hcc/papers/johnson-laird_r.htm .
Lohse, E.S. (2002). Measuring prehistory strategies: flakes, symmetries and balance in stone tools. Paper presented at the Ninth International Conference on Hunting and Gathering Societies (CHAG 9), Edinburgh, September.
Lohse, E.S. & Sammons, D. (1998). Digital Stones: A Guide to Analysis of Stone Tools. Interactive CD-ROM.
Lohse, E.S. & Sammons, D. (2002) Digital Stones: Teaching an archaeological lab course on-line. Internet Archaeology, 12. Available by subscription at http://intarch.ac.uk/journal/issue12/lohse.html
Lohse, E. S., Sammons, D., & Schlader, R. (2001). Anthropology 491: Teaching an on-line laboratory course. In Proceedings of ED-MEDIA 2001, edited by C. Montgomerie and J. Viteli, pp. 1628-1630.
Marchese, T.J. (1997). The New Covnersations About Learning: Insights from Neuroscience and Anthropology, Cognitive Science and Work-Place Studies. In Assessing Impact: Evidence and Action, pp. 79-95. Washington, D.C.: American Association for Higher Education.
Marton, F. and R. Saljo. (1976). On Qualitative Differences in Learning: 1. Outcome and Process. British Journal of Educational Psychology, 46, 4-11.
Pringle, M.J. (2000). The Use of Virtual Reality for the Visual Presentation of Archaeological Information. Ph.D. dissertation, Cranfield University. Retrieved November 17, 2004 from http://www.pringle.org/com/webthesis/contents.html
Pringle, M. (2001). Using Virtual Reality to improve public access to heritage databases over the Internet. In Computing Archaeology for Understanding the Past, CAA 2000, British Archaeological Reports International Series. Retrieved November 17, 2004 from http://www.english-heritage.org.uk/filestore/pastscape/background/caa200/caa2000.html
Pringle, M.J. & Moulding, M.R. (1997). Applications for Virtual Reality, and associated information technology, in the illustration of archaeological material. Retrieved November 17, 2004 from http://www.pringle.org/com/aais/aais.html
Third International Mathematics and Science Study. Successive Reports from Kluwar Academic Publishers, Boston/Dordrecht, London.
Trochim, W.M.K. (1989). Concept mapping: Soft science or hard art? Evaluation and Program Planning, 12, 1: 87-110.