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Teaching Abstract Data Type Semantics with Multimedia* Glenn D. Blank, Edwin J. Kay, William M. Pottenger Jeffrey J. Heigl, Soma Roy and Shreeram A. Sahasrabudhe.

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Presentation on theme: "Teaching Abstract Data Type Semantics with Multimedia* Glenn D. Blank, Edwin J. Kay, William M. Pottenger Jeffrey J. Heigl, Soma Roy and Shreeram A. Sahasrabudhe."— Presentation transcript:

1 Teaching Abstract Data Type Semantics with Multimedia* Glenn D. Blank, Edwin J. Kay, William M. Pottenger Jeffrey J. Heigl, Soma Roy and Shreeram A. Sahasrabudhe Computer Science & Engineering Department Lehigh University 19 Memorial Drive West Bethlehem PA 18015 *The CIMEL project is funded by National Science Foundation (Grant Number EIA-0087977)

2 Abstract CIMEL (Constructive, collaborative, inquiry-based multimedia e-learning) is a multimedia framework for Computer Science courses We developed units on inheritance and dynamic binding and another on Abstract Data Types (ADTs). An experimental study in a software engineering course shows that multimedia produces a significant learning effect for both objective and task knowledge.

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4 Why Abstract Data Types? OO analysis specifies classes and their relationships (as UML diagrams). OO design should specify the semantics of the classes and their functions or methods. ADTs represents the semantics of classes formally and explicitly. Pre-conditions and post-conditions specify a contract between clients and supplers

5 The Problem Design by contract using abstract data types is a good idea! But students have trouble understanding it, especially applying it. Semantics is hard: lectures and books aren’t enough

6 Our approach Multimedia presents the ideas: graphical personae with full audio, animations, and simple exercises. Interactive simulations and constructive exercises let students learn by doing.

7 A constructive interactive exercise SHOW ME Constructive means learning by building systems, with immediate, visual feedback.

8 Inquiry Based Inquiry-based means learning by doing exploratory research. A reference librarian, represented by a persona, shows students how to use online library databases and dynamically mined emerging trends.

9 Collaborative learning lets students interact with instructors and librarians, via live links and remote-controlled "show me" sessions, or by reviewing a multimedia FAQ of recorded "show me" sessions. Collaborative

10 Show me collaborative tool

11 A track driven learning process Dynamic Tracks User Interface has options bar at bottom and draggable content menu on left. Below is a UI for multi-tracking of learning content. Given default paths for different courses, instructors and students can then create their own tracks, selecting chapters, sections and/or screens.

12 List of Templates & Exemplars designed and used in CIMEL project: Indexed list of items 2Drag and drop exercises 3Multiple choice exercises 4Lesson tracking 5Dynamic Sound 6Dynamic graphics 7End of chapter Quizzes ….. and many more Templates facilitate development and help maintain consistency. Developers adapt Flash Smart Clips, which automatically generate new content.

13 Integrating BlueJ in CS1 course

14 Using the tools menu to access a Java program

15 Exercise reviewing how array values are used in a loop

16 Emerging Trends detection guides identification of emerging topics in textual data. As shown, “Components” is an emerging topic, with a noticeable increase in cluster size from 1995 through 1998. Cluster visualization gives a closer look at how trends emerge across time. Visualization shows the relationship between different concepts that represent trends. Evaluation is a key part of our project. We conducted experiments, surveys and focus groups to determine whether the alpha version of our multimedia actually improves learning and what improvements should be made for our beta version.

17 Multimedia Lecture Multimedia No Lecture Experiment Spring 02 SE Course 1.Homework problem (task) 2.Online post-test (objective) No Multimedia Lecture No Multimedia No Lecture 72 upper level undergraduates

18 Results The results from the experiment are very promising! (and interesting) The lecture did not have a significant effect! Multimedia Lecture Multimedia No Lecture No Multimedia Lecture No Multimedia No Lecture 14.7 76.3 12.3/20 68.8/100 12.29 (task) 15.39 (objective) 1.11 (task) and 0.55 (objective) Task Objective Students getting multimedia scored higher on both assignment and post- test!

19 A closer look… With or without multimedia, most students missed an important component of the assignment: Reusing a given ADT (List) to construct the semantics of a new ADT (Bowl). It appeared that students did get concepts of ADTs and ADTs as collections. But they “connect the dots” and use constructive semantics.

20 New and improved… Closer look at result led to redesign of the multimedia: We redesigned the multimdia: Rearranged the material by making ‘ADT for collections’ as a separate chapter. And added another exercise that explicitly gets learners to solve problems from existing ADTs.

21 The New Exercise

22 Multimedia Effects The overall quality of the final projects in the course have improved, indicating that students are better understanding the concepts – being aided by multimedia. Multimedia also helps fill in gaps between concepts and implementation details. For instance, it can build the bridge between UML diagram and the actual coding. With each experiment, focus group and feedback, we continue to refine our multimedia and the way it is presented to better help the students in grasping the concepts.

23 Inquiry-based learning The module is a methodology for emerging trend detection. It has been tested in two experiments consisting of undergraduates and graduates respectively. With a precision of 95% in the undergraduate class and 99% in the graduate class, the students using the module were significantly successful than those not using it.

24 Constructive, collaborative, Inquiry-based, Multimedia E-Learning* * Funded by the National Science Foundation (Grant No. EIA-0087977)


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