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Milo Koretsky

Web-based Interactive Science and Engineering Learning Tool

Welcome to the Web-based Interactive Science and Engineering (WISE) Learning Tool, an innovative classroom learning tool that promotes an active learning environment and provides an opportunity for real-time assessment of student's understanding of core concepts.

If you already have an account and/or want to leave anonymous feedback about a class, you can click "Log In" to the left.

We are grateful for funding by the LL Stewart Scholars Program and an OSU Teaching and Learing Innovation Grant. We also acknowledge the help and support of the COE IT team.

The undergraduate engineering classroom of the 21st century has the opportunity to enhance student learning through the effective integration of technology into the classroom.  In an effort to promote the use of advanced technology to develop a more engaging and innovative learning experience for students, the College of Engineering (COE) at Oregon State University implemented a Wireless Laptop Initiative in 2002 which allowed large-scale implementation of wireless technology in the classroom and required all undergraduate engineering students to own a laptop.  To support this initiative, we have developed the Web-based Interactive Science and Eineering (WISE) Learning Tool.

The WISE learning tool allows an instructor to pose to the class questions that probe for conceptual understanding and supports a variety of student response types including: multiple choice answers, multiple choice with short answer follow-up, numerical answers, short answers, and Likert-scale surveys. We also plan to incorporate interactive applets.

WISE is designed for use in the context of a learner centered class, based on active learning. It is designed to allow real-time formative assessment by the instructor. After the students have submitted a response to an activity, the instructor can review a summary of the results with the class. Depending on the class response, the instructor can choose an appropriate method (e.g. peer instruction, instructor explanation) to reinforce or correct the response.
For example, a screenshot of the results screen is shown in Figure 1. The results shown by the orange and black bar graph represent the entire classes response to the multiple choice question posed. This result is automatically generated by the software. Instructors can also select among the entire classes’ short answer follow-ups. This specific concept question shown in Figure 1 was included in a pre-assessment quiz for ENGR 221. Three follow-ups were selected by the instructor. Active learning was promoted during the class discussion of quiz answers which was intended to prime students to look for specific concepts during the rest of the term.
	Figure 1.

It is web-based for a number of reasons. First, this allows for the software to be centrally managed. A change can be made to the webserver or database server and takes effect immediately. Students and teachers don't need to download and install the latest version. Second, it is better for security. Very little processing is done on the students computer, so it is difficult for students to modify or trick the program. Third, this setup maximizes compatibility and ease of use for users. The college of engineering requirement doesn't specify the make of wireless laptop a student should purchase. While not all computers have windows or java, they usually have a web-browser.

The logo represents the cyclic model of knowlege development. The cyclic model of knowlege is an adaptation from a report on how to achieve mathematics proficiency in K12 education in the US ( Ball, 2003); it has been incorporated into NSF requirements for educational grants. The model describes a process for creating new educational interventions that includes conducing educatonal research, assessing learning, evaluating the intervention and incorporating these learnings into developing faculty expertise.

Engineering students or faculty, at the moment, are placed into whatever class they select as students after logging in with their engineering username and password. Please contact your instructor if you do not have an account or cannot access the system. The instructor can add students that don't have valid engineering usernames and passwords.

Instructors must sign up for an instructor account.

One way to provide in-class assessments is through the use of a personal response system, typically referred to as “clickers.” While this process has been shown to be effective (Reay, 2005), (Chen, 2006) and is used by several classes at OSU, it also has its limitations. Clickers are limited to multiple choice questions. Appropriate questions can be difficult to construct, and the development of appropriate “distracters” (answers that have been identified to be associated with common misconceptions) can be a barrier.

A laptop-based response system provides much more versatility in activity development and class room instruction. WISE allows short-answer follow-ups to multiple choice questions. The short answers can allow instructors to identify misconceptions directly from students, rather than inferring through distracters. Pedagogically, it gives students opportunities for metacognition through reflection ( Svarovsky , 2006 ), and, therefore, enhances the learning in the exercise. There is activity in the education community in developing in-class simulations and virtual experiments to assist students to visualize and experiment with the science and engineering of a particular topic ( Burke, 1998 ). A program like WISE can integrate these learning activities directly into the instruction. WISE also allows for the integration of homework activates ( Chang, 2004 ), real-world examples, and remedial tutorials. Finally, unlike “clickers,” instructors have the capability to use it in very different ways from week to week – keeping the instruction “fresh.”

In a sense, WISE can be viewed as “a clicker on steroids.”

Many engineering classes emphasize student problem-solving skills almost to the exclusion of the understanding of underlying concepts. It has also been shown that, with traditional instruction, students are better rewarded by rote learning than by conceptual understanding ( Elby, 1999 ). In fact, one study has shown that chemistry students demonstrated a 38% success rate on conceptual problems as compared to a 95% rate on numerical problems ( Haláková, 2007 ). However, it has also been shown that the lack of conceptual understanding severely restricts the student’s ability to solve a new problem ( Hestenes, 1992 ).

Alternatively, concept-based instruction is based on the premise that the understanding of concepts is central to understanding a subject and extending knowledge to new problems and areas ( Mazur, 1997 ). By incorporating concept based instruction, students can transition from problem solving by example - - where they seek a one to one correspondence between an example problem they had been shown and the problem they are given - - to a higher level of cognition where they solve problems by applying the fundamental principles covered in the course to any of a variety of entirely new problems.

In terms of Bloom’s Taxonomy of Education Objectives ( Bloom, 1956 ), a threshold from lower to higher level learning lies in the transition from Application, where concepts are employed to solve problems in new situations to Analysis, which includes the breaking down of information into its component parts, and then understanding these individual parts and the relationships between them. At OSU and elsewhere, it is in their Engineering Science courses, through the rigors of problem solving, that engineering students are pushed beyond Application to Analysis. It is necessary for students to master Analysis before they can progress to the Synthesis and Evaluation that their capstone senior-level design and laboratory experiences are intended to develop. On the other hand, those students who manage to get through their Engineering Science courses while “stuck” in the Application phase tend to memorize the algorithms for solving assigned problems without understanding the underlying concepts. They are unlikely to show any real cognitive growth in the open-ended capstone courses during their senior year.  Additionally, they tend to fail to see how the material they are studying connects to the “real world”.

The intent in developing the WISE Learning tool is that, through active learning and conceptual understanding, more students will transition into the higher level cognitive domain.

Bloom, B.S., ed.  Taxonomy of Educational Objectives:  The Classification of Educational Goals.  Handbook I: Cognitive Domain.  New York, Longman, 1956.

Burke, K.A, T. J. Greenbowe, and M. A. Windschitl, “Developing and using conceptual computer animations for chemistry instruction,” Journal of Chemical Education, 75, 1658-1661 (1998).

Chang, K. Kelvin, Beth Ann Thacker, Richard L. Cardenas, and Catherine Crouch, “Using an online homework system enhances students' learning of physics concepts in an introductory physics course,” Am. J. Phys., 72, 1447 (2004).

Chen, John C.,  Dexter C. Whittinghill and Jennifer A. Kadlowec, “Using Rapid Feedback to Enhance Student Learning and Satisfaction” 36th ASEE/IEEE Frontiers in Education Conference, SD2-13 - SD2-18 (2006).

Elby, Andrew “Another reason that physics students learn by rote,” Am. J. Phys, 67, S52 (1999).

Haláková, Zuzana and Miroslav Proksa, “Two kinds of conceptual problems in chemistry teaching,”Journal of Chemical Education, 84, 172-174 (2007).

Mazur, E, Peer Instruction, Prentice Hall, 1997.

Reay, Neville W., Lei Bao, Pengfei Li, Rasil Warnakulasooriya, and Gordon Baugh, “Toward the effective use of voting machines in physics lectures,” Am. J. Phys. 73, 554 (2005).

Svarovsky, G.N. and D.W. Shaffer, “Design meetings and design notebooks as tools for reflection in the engineering design course,” 36th ASEE/IEEE Frontiers in Education Conference, MSG-7 - MSG-12 (2006).