CS Education Research at
the University of Texas at Austin
Nell B. Dale
for CSERGI 2 Workshop
October 25, 1998
About Our Group
- Since 1990, this group has held regular weekly seminar meetings at
which we discuss articles, have guest lectures, design and discuss research
projects, and pursue other activities related to CS Education.
- The group includes several faculty members, including Vicki L. Almstrum,
Nell Dale, Suzy Gallagher, Mary Dee Harris, Rich Mallory, Roger Priebe,
Hamilton Richards, and Laurie Honour Werth.
- A primary goal of the group is to support and encourage doctoral students
who are pursuing topics related to CS Education. These include Dawn Stokes,
Meng-Jung Tsai, Mengping Tsuei, Garry White. Lisa Kaczmarczyk will join
the group as she begins doctoral studies at UT Austin in January 1999.
- One of the group's strengths is the set of affiliates we have at other
Universities. These include Laura J. Baker, Dawn Cizmar, and Barbara B.
Owens of St. Edward's University, Austin, TX; Debra Burton Farrior of Victoria,
TX; J. Paul Myers, Jr. of Trinity University in San Antonio, TX; Henry
Walker of Grinnell College in Grinnell, Iowa; and Cheng-Chih Wu of National
Taiwan Normal University in Taipei, Taiwan.
- The group's web page is located at http://www.cs.utexas.edu/users/csed/.
Research areas of current interest:
The Cloze Technique for Test Questions
Nell Dale
Computer Sciences Department
University of Texas @ Austin
The cloze technique replaces every nth word in text with a blank. A student's
reading skills can be assessed by how many words the student correctly replaces.
The reading difficulty of the text can be assessed by how many words students
are able to replace. Can this technique be used to construct test questions?
A pilot study
was reported during the first CSERGI workshop.
Impact of Strategic Learning on Taiwanese Eighth Graders'
Computer Achievement, Computer Attitudes, and Computer Anxiety in a Cooperative
Learning Context
Meng-Jung Tsai
Doctoral Research
Procedure
Group 1
Strategic training treatment |
Group 2:
Group learning treatment |
Group 3:
Strategic training treatment +
Group learning treatment |
Group 4:
Traditional approach |
Instruments
CILM-SR |
Literacy Measure developed by Turner, Sweany and Husman in 1998 |
CAS |
Computer Attitude Scale developed by Nickell and Pinto in 1986 |
CARS |
Computer Anxiety Rating Scale developed by Heinssen, Glass, and Knight in
1987 |
LASSI-HS |
Learning and Study Strategies Inventory developed by Weinstein and Palmer
in 1990 |
Order of Topic Presentation:
General to Specific or Specific to General?
Ham Richards
Computer Sciences Department
The University of Texas at Austin
Haskell is being used in the CS1 course for majors. Is it better to introduce
lists, list comprehensions, and prelude functions such as map, filter
and foldr, before explicitly introducing recursive functions over
lists or is the reverse order better? This is a classic case of top-down
versus bottom-up presentation.
Computing Students' Understanding
of Mathematical Logic
Vicki Almstrum
Department of Computer Sciences
The University of Texas at Austin
In her doctoral research, Vicki showed that students who had taken the
Advanced Placement Examinations in Computer Science had more difficulty
with problems strongly related to mathematical logic than they generally
had with questions that were not strongly related to mathematical logic.
Several follow-up questions are under consideration, including:
- Do these same results occur in the data from other years of the APCS
exams?
- What else can be said about the reliability and validity of the results
from the content analysis procedure, which was used to partition the APCS
questions according to how strongly they were related to mathematical logic?
- Can the content analysis procedure be adapted to other settings?
- How well do students perform on the questions identified as strongly
related to mathematical logic in contexts outside of the APCS setting?
How do these results correlate with the students' backgrounds and attitudes?
(Work in progress with Nilanjana De.)
Other interests
PTL (Propositional Logic Test)
- Developed by science education faculty and students at Rutgers University
- Assesses a person's ability to process propositional statements
- A 16 item instrument where, in 15 minutes, the participant interprets
truth-functional operators by identifying instances that are consistent
or inconsistent with a stated rule
- Some research questions related to the PLT:
- Can the PLT be used as a predictor to help advise students about their
likelihood of success in computing studies?
- In work with Paul Baffes, Vicki Almstrum is investigating the use of
automatic student modeling and bug library construction using theory refinement
in the context of the PLT.
- In her doctoral research, Youngju Kim investigated the reasoning ability
and achievement of college level students enrolled in a logic class in
computer science. The PLT was the instrument that she used to measure students'
reasoning abilities. A current doctoral student, Garry White, has been
developing a proposal that would extend this research to other settings.
Learning styles
- Students perceive and process information in different ways. Learning
Styles Inventories are instruments that attempt to categorize students'
cognitive learning styles. Four LSIs of interest are:
- Solomon/Felder
- Kolb
- Honey Mumford
- Gragoric
- Some research questions related to LSIs:
- In what ways do the scales of the various LSIs relate to one another?
- How can the results of an LSI be used to advise students?
- Are students with a particular learning style more likely to succeed
in computer science?
Learning strategies
- LASSI , the Learning and Study Strategies Inventory, can be used
to measure students learning strategies in ten areas: time management,
anxiety, concentration, information processing, selecting main ideas, study
aids, self-testing, and test strategies.
- Some research questions related to learning strategies are:
- Are students with certain learning strategies more likely to succeed
in computer science?
- How can we in our computer science classes improve the learning and
study strategies of our students?