
BC:

PER: Problem Solving I

Location:

HC 3023 & 3023A 
Date:

Monday, Aug.01 
Time:

1:00PM  2:30PM

Presider:

Paul Nienaber,

CoPresiders(s):

None

Equipment:

N/A



BC01:

Tutorials to Facilitate Physics Problem Solving with Differentiation and Integration

Location:

HC 3023 & 3023A 
Date:

Monday, Aug.01 
Time:

1:00PM  1:10PM

Author:

Dehui Hu, Kansas State University
7855321612, dehuihu@phys.ksu.edu

CoAuthor(s):

Joshua Von Korff, N. Sanjay Rebello

Abstract:

Students in introductorylevel physics encounter several difficulties when solving physics problems involving differentiation and integration. Physics instructors tend to assume that students have the prerequisite mathematical skills for success in the course, however, research has shown that most students do not know how to apply mathematical tools in a physics context. Based on the knowledge of the difficulties students with the use of differentiation and integration in physics encoutered from previous studies, we are developing instructional materials aimed at facilitating students to address these difficulties in several topics in introductory physics. We have implemented these materials in group problemsolving sessions aimed at enabling students to learn the mathematical concepts of tangent lines, slope, Riemann sum, and approximation in a physics context. We present a discussion about student difficulties on those concepts and the development of our instructional materials.

Footnotes:

This work is supported in part by U.S. National Science Foundation grant 0816207.



BC02:

The Influence of Hints and Training on Student Resource Selection

Location:

HC 3023 & 3023A 
Date:

Monday, Aug.01 
Time:

1:10PM  1:20PM

Author:

Joshua S. Von Korff, Kansas State University
7855321612, vonkorff@phys.ksu.edu

CoAuthor(s):

Dehui Hu, N. Sanjay Rebello

Abstract:

We consider physics problems that require students to combine their existing resources in new ways. When students do this in the context of integration and differentiation, they have many procedures, concepts, and representations to choose from. In addition, they may have varying degrees of understanding about the procedures they invent. We examine students' resource selection in problem solving situations, using an online environment to control and monitor their progress through a series of hints. Over the course of a 30minute testing period, students work through a single problem; initially inventing their own strategies, then following our suggestions toward particular solutions. We will present results from our assessment of students' naïve understanding, as well as the impact of cues and training after a 50minute practice session prior to the test. We will also describe students' ability to learn new ways of thinking about the problem.

Footnotes:

This work is supported in part by U.S. National Science Foundation grant 0816207.



BC03:

Do Prescribed Prompts Prime Sensemaking During Group Problem Solving? Part One

Location:

HC 3023 & 3023A 
Date:

Monday, Aug.01 
Time:

1:20PM  1:30PM

Author:

Mathew A. Martinuk, University of British Columbia
7788366366, martinuk@physics.ubc.ca

CoAuthor(s):

Joss Ives

Abstract:

Many researchers and textbooks have promoted the use of rigid prescribed strategies for encouraging development of expertlike problemsolving behavior in novice students. The UBC Physics 100 course has been using contextrich problems with a prescribed fivestep strategy since 2007. We have been analyzing audio recordings of students during group problemsolving sessions to analyze students' epistemological framing based on the implicit goal of their discussions. By treating the goal of "understanding the physics situation" as "sensemaking," we analyze the effectiveness of structured prompts intended to promote a shift to a sensemaking discussion. This talk will describe the setting and research methods, and a subsequent talk will discuss the analysis and results.

Footnotes:

None



BC04:

Investigating Sequencing Effect on Biomedical Physics Problem Solving

Location:

HC 3023 & 3023A 
Date:

Monday, Aug.01 
Time:

1:30PM  1:40PM

Author:

Bijaya Aryal, University of MinnesotaRochester
5072588216, baryal@umn.edu

CoAuthor(s):

Robert L. Dunbar

Abstract:

This study focused on the effect of varying the sequence of problem solving and laboratory activities on the students' ability to solve subsequent biomedical contextual physics problems. A series of laboratory and problem solving activities were designed using concrete physical situations. Following the introduction of specific physics concepts, students worked in groups to complete related laboratories and problem solving activities. The order of problem solving and laboratory activities was regularly altered throughout the semester. Subsequently, the students were asked to solve related contextual biomedical physics problems. The result of the study indicated that altering the sequence of activities had a measurable impact on students' contextual problem solving performance and strategies.

Footnotes:

None



BC05:

How to Improve Transfer from Difficult Worked Examples by Designing a 'Good Looking' Animated Solution

Location:

HC 3023 & 3023A 
Date:

Monday, Aug.01 
Time:

1:40PM  1:50PM

Author:

Zhongzhou Chen
The University of Illinois at Urbana–Champaign
2177218411, zchen22@illinois.edu

CoAuthor(s):

Gary Gladding

Abstract:

It is well known that transfer from worked examples to new problems can be very hard for students. The goal of this research is to promote transfer by improving the quality of the example solution. According to our experience, elaborate verbal explanation often seems to have little, if not negative, effects on transfer. Therefore, we focus on designing a better visual representation. Based on knowledge from grounded cognition research, we designed several animated multimedia solutions for some difficult physics problems, in which the underlying logic is illustrated through visual perception. When compared to two other very similar versions of animated solutions that lack the critical perceptual elements, the designed solutions significantly improved transfer of the underlying physics principles to harder problems. Moreover, transfer is improved even when the target problem involves largely abstract logical reasoning, and little visualspatial reasoning.

Footnotes:

None



BC06:

The Impact of Sample Size in Using IRT with FCI

Location:

HC 3023 & 3023A 
Date:

Monday, Aug.01 
Time:

1:50PM  2:00PM

Author:

Li Chen
School of Electronic science and engeering, Southeast University
6142922450, chenli.seu@163.com

CoAuthor(s):

Jing Han, Liangyu Peng, Yan Tu, Lei Bao

Abstract:

Item Response Theory is a useful tool for analyzing quantitative data. The sample size will impact the uncertainty of the estimated parameters. It is then important to find out the approximate minimum sample size, with which reliable results can be calculated. In this study, we choose R (with its LTM package) to estimate the parameters with different sample sizes, which are randomly selected from the college students' FCI data collected at The Ohio State University. The total number of the data is 3139. The results show an exponential relationship between sample size and the mean difference of the results obtained with subsets of the data. When sample size is larger than 1600, the difference is tolerable for most items and the mean total difference can be controlled within 5%. This can provide useful guide for future data analysis using IRT.

Footnotes:

Supported in part by NIH Award RC1RR028402 and NSF Awards DUE0633473 and DUE1044724



BC07:

The Effect of Problem Format on Students' Answers

Location:

HC 3023 & 3023A 
Date:

Monday, Aug.01 
Time:

2:00PM  2:10PM

Author:

Mark Ellermann, Texas Tech University
8067423971, mark.ellermann@ttu.edu

CoAuthor(s):

Beth Thacker, Keith West

Abstract:

The same problem written in multiple formats was administered as a quiz in the large introductory physics sections in both the algebrabased and calculusbased classes. The formats included multiple choice only, multiple choice and explain your reasoning, explain your reasoning only, ranking and explaining your reasoning, and a few others. We present the data.

Footnotes:

This project is supported by the NIH grant 5RC1GM09089702.
Sponsored by Beth Thacker.



BC08:

What Students Learn When Studying Physics Practice Exam Problems

Location:

HC 3023 & 3023A 
Date:

Monday, Aug.01 
Time:

2:10PM  2:20PM

Author:

Witat Fakcharoenphol
University of Illinois at Urbana Champaign
2178984854, fakchar1@uiuc.edu

CoAuthor(s):

Timothy J. Stelzer

Abstract:

We developed a webbased tool to provide students with access to old exam problems and solutions. By controlling the order in which students saw the problems, as well as their access to solutions, we obtained data about student learning by studying old exams problems. Our data suggest that in general students learn from doing old exam problems, and that having access to the problem solutions increases their learning. However, the data also suggest the depth of learning may be relatively shallow. In addition, the data show that doing old exam problems provides important formative assessment about the student's overall preparedness for the exam, and their particular areas of strength and weakness.

Footnotes:

None



BC09:

Using ProblemSolving Computer Coaches to Explore Student DecisionMaking Difficulties

Location:

HC 3023 & 3023A 
Date:

Monday, Aug.01 
Time:

2:20PM  2:30PM

Author:

Qing Xu, University of MinnesotaTwin cities
6126259323, qxu@physics.umn.edu

CoAuthor(s):

Ken Heller, Leon Hsu, Andrew Mason

Abstract:

The Physics Education Group at the University of Minnesota has been developing Internet physics coaches to help students improve their problemsolving skills in introductory physics. In this talk, we analyze keystroke data collected from students' usage of the computer programs, including the identity and timing information for all students' keystrokes and mouse clicks while using the programs, as well as derived information such as the average time spent on each module. We use the data to try to determine how students use the computer programs, where they might have the most difficulty, and details of their decisionmaking behavior during the problemsolving process. Other data sources such as students' written solutions will be used as a consistency check.

Footnotes:

None


