Outcomes of Using an Infinitely Explorable Online Learning System

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Outcomes of Using an Infinitely Explorable Online Learning System Franco Capaldi 1 , Devin R. Berg 2 1 Department of Civil Engineering, Merrimack College, North Andover, MA 2 Engineering & Technology Department, University of Wisconsin – Stout, Menomonie, WI ASEE Annual Conference 26 June 2013 1

Transcript of Outcomes of Using an Infinitely Explorable Online Learning System

Outcomes of Using an Infinitely Explorable Online Learning System

Franco Capaldi1, Devin R. Berg2 1Department of Civil Engineering, Merrimack College, North Andover, MA

2Engineering & Technology Department, University of Wisconsin – Stout, Menomonie, WI

ASEE Annual Conference 26 June 2013

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Students explore problems in a guided manner, promoting critical thinking

skills and knowledge retention.

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𝑀𝐴 = 1 𝑁 𝑚

𝑀𝐴 = 𝑟 × �⃗�

𝑀𝐴 = �⃗� d

Problems can be formulated to provide 3D exploration of realistic

situations.

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The software provides flexibility through interpretation of student input.

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For example, vector notation can be used to describe position, forces, etc.

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The software provides “word” descriptions of equations.

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𝑟𝐴/𝐷 = −25 𝑖 𝑖𝑖

“The position vector from point D to point A is equal to the negative of the scalar value 25 multiplied by the unit vector i with units of inches”.

becomes

Student answers can include explanatory text...

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… or figures such as free body diagrams.

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Effectiveness was evaluated through a preliminary study at Merrimack College

and UW-Stout.

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At Merrimack: Two classes -1 treatment (n=12) -1 control (n=7) Evaluated through semester using exams

At Stout: Two classes -1 treatment (n=21) -1 control (n=23) Evaluated using pre- and post-FCI

Student performance throughout semester was greater for treatment group.

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Section Initial Assessment

Midterm 1 Vectors, Forces

Midterm 2 Moments, Free body diagrams

Midterm 3 Moment of inertia, Centroids

Final Exam

Treatment Group (n=12)

𝟑𝟑 ± 𝟑𝟏 𝟖𝟏 ± 𝟑𝟏 𝟏𝟑 ± 𝟕 𝟖𝟖 ± 𝟑𝟏 𝟖𝟕 ± 𝟕

Control Group (n=7)

𝟑𝟑 ± 𝟑𝟏 𝟕𝟏 ± 𝟐𝟑 𝟕𝟑 ± 𝟑𝟑 𝟕𝟏 ± 𝟑𝟑 𝟖𝟐 ± 𝟑𝟏

Students learned to use the software more effectively with time.

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Homework 1 Homework 2 Homework 3

Percent of total answers which contained program

syntax errors

12% 41% 52%

Percent of non-syntax errors which were correct /

incorrect statements

83%/17% 46%/54% 21%/79%

Percent of correct answers which were required for

solution

93% 67% 53%

Percent of correct answers which were hypotheses 7% 33% 47%

The treatment group showed greater overall score improvement on FCI.

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Treatment (n=21) Control (n=23)

Students want intuitive input with fewer restrictions.

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… and they want the answers!

Handling of syntax errors was a significant concern during the semester.

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Student Entry Category

Σ𝐹𝑥 = 𝐹𝐴𝑥 + 12 𝑁 sin 27 𝑑𝑑𝑑 − 𝐹𝐹 Required for solution

∑𝐹𝑥 = 𝐹𝐴𝑥 + 12 [N sin(27 [deg]) – FB Program syntax error: ‘12 [N’.

𝑠𝑖𝑖 27 𝑑𝑑𝑑 = 0.454 Correct hypothesis:

∑𝐹𝑥 = 𝐹𝐴 + 5.448 𝑁 − 𝐹𝐹 Incorrect statement:

Room for improvement through…

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better handling of student input.

making use of student training.

an adaptive algorithm to enhance student interaction.

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3D interaction with problems was a popular feature

Things that worked well included…

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testing of intermediate steps for difficult problems.

3D exploration helped with vector and FBD problems.

better performance across a wider range of students.

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