This document summarizes a collaborative project between computer science and journalism students at The College of New Jersey to engage journalism students in computational thinking. The project involved the students collaborating to build an online system to help a nonprofit address environmental issues. Assessment found the collaborative project increased journalism students' computational self-efficacy and motivation to learn computational skills relevant to their field. Future research is needed on better integrating computational thinking throughout journalism education.

1. Collaborating Across Boundaries
to Engage Journalism Students in
Computational Thinking
Project Funded through NSF Award # 1141170
PIs: S. Monisha Pulimood (Computer Science) and
Kim Pearson (Journalism)
Evaluator: Diane Bates (Sociology)
The College of New Jersey
AEJMC August 8, 2015

2. Journalism students need
computational thinking
Hewett, Jonathan. Data journalism, computational journalism and computer-assisted reporting:
What’s the difference? Hackademic: Journalism Education (and More) November 12, 2014. Accessed March 12, 2015.
http://hackademic.net/2014/11/12/data-journalism-computer-assisted-reporting-and-computational-journalism-whats-
the-difference/
“Computational thinking for everyone means being able to understand which aspects of a
problem are amenable to computation, evaluate the match between computational tools and
techniques and a problem,
understand the limitations and power of computational tools and techniques, apply or adapt
a computational tool or technique to a new use, recognize an opportunity to use
computation in a new way, and
A pply computational strategies such as divide and conquer in any domain. “
Mark Guzdial
Source: http://bit.ly/1yPRXKW
Guzdial, M. A Definition of Computational Thinking from Jeannette Wing.
Computing Education Blog, Mar. 2011

3. Collaborating Across Boundaries to Engage Undergraduates in
Computational Thinking
Hypothesis: To increase motivation toward, and interest in, computing
careers, undergraduate students must be immersed in multidisciplinary
collaborative experiences where they are creators of computational
solutions and internalize the relevance of and interconnectedness between
classroom learning and the community they live in.
Journalism education objectives:
• Increase journalism students’ computing self-efficacy
• Improve journalism students’ understanding of applicability of computing
methods and tools to their fields
• Expose journalism students to interdisciplinary computing collaborations

4. Research base
o Growing support for CS education in
journalism curriculum (Stray, Bradshaw,
Hernandez Royal)
o Pipeline, culture problem for
data/computational journalists mirrors
problems facing all computing fields (Guzdial,
Wolz, Royal, Johnson, Margolis)
o CS education in journalism may be path to
broadening computing (Wolz, et.al., Royal)
4

5. The Pilot Project
o Affordable housing and food insecurity are huge
problems in urban areas.
o Groups like Habitat for Humanity face challenge of
redeveloping land that may be polluted.
o Computer science, journalism students are collaborating
HH to develop an online system called SOAP (Students
Organizing Against Pollution).
 To help HH estimate costs for cleaning up properties
 To empower citizens to learn, share, and contribute pollution
data, and become active participants in environmental
advocacy and public policy deliberations.
 HH is an expert source and starting point for reporting
5

6. The Pilot Project
o Builds on the cooperative expertise
model of distributed CS education.
(Way, et. Al.)
o Collaborating class sessions are held
in the same timeslot but
independently.
o Classes meet 3-4 times during the
semester to brainstorm, share
progress reports and plan next steps.
o Class visits by Tom Caruso, Executive
Director of Habitat for Humanity
(HH) and Nicky Sheats, Director of
Center for Urban Environment
(expert on environmental justice).
o Field trip to Trenton, NJ to visit HH
office, acquired properties, and
contaminated sites.
6

7. Collaborating classes – 2013-15
Semester JPW/IMM class Computer
science class
Spring 2013 Blogging and
social media
Software
engineering
Fall 2013 Health and
environmental
journalism
Database
Systems
Serious games
for news
Software
engineering
Spring 2014 Future of the
news
Software
Engineering
Fall 2014 Health and
environmental
journalism
Software
engineering
Spring 2015 Social media
strategies
Software
engineering7

8. The Pilot Project
o Assignments and class projects are
based on “problem”.
o CS class designs and develops
modules to address concerns and
needs raised by the journalism
class, Dr. Caruso and Dr. Sheats.
o Journalism class researches
trusted sources for data and
explores new technologies and
techniques for storytelling, data
interpretation and improving user
experience.
8

9. Finding our own “ghost factories”
9

10. Artifacts
GitHub, Google spreadsheet, Crowdmap used for
shared communication and information collection
Game design students used UNITY engine to build
games simulating challenges of finding safe sites to
build homes. Content created and archived for
incorporation as modules are ready.
Each class provides feedback and consultation on
the artifacts being created by the other classes.

11. 11
Work in progress handed
off from semester to
semester eg:
customizable twitter tool,
blogging module,
legislation module.

12. Assessing Outcomes:
Operationalization
o All students were asked a series of eight
questions, derived from ABET’s General and
Program-Specific (Computer Science) Student
Outcomes Criteria for Accrediting Computing
Programshttp://www.abet.org/accreditation-
criteria-policies-documents/
o Items were derived from Criteria from 2012-
2013 Accreditation Cycle Document, but these
had not changed as of the most recent 2015-
2015 document.

13. Assessing Outcomes:
Operationalization
o The last three items indicated below are based on
Dr. Jeannette Wing’s definitions of computation
thinking, which have been widely distributed in a
variety of publications.
o For journalism, items were added that were
derived from the Accrediting Council on Education
in Journalism and Mass Communications (ACEJMC)
Accrediting Standards on Curriculum and
Instruction
https://www2.ku.edu/~acejmc/PROGRAM/STANDA
RDS.SHTML

14. Assessing Outcomes:
Operationalization
On both pre-test and post-test, student were asked “to what extent do you
agree or disagree with each of the following:” with response categories of:
Strongly Agree (coded 4), Agree (3), Disagree (2), or Strongly Disagree (1)
with the following items:
• I can apply knowledge of computing appropriate to my major.
• I can analyze a problem, and then identify and define the computing
requirements appropriate to its solution.
• I understand the impact of computing on society.
• I can use current computing techniques, skills, and tools necessary in
careers for which my major prepares me.
• I can collaborate with others to design and develop computer based tools
and technologies appropriate to careers for which my major prepares me.
• I can use abstractions
• I can use logical thinking
• I can use algorithms

15. Assessing Outcomes:
Operationalization
o There are between 107-113 valid cases for each
of these items.
o Reliability analysis of these items as a measure
of computational thinking is indicated by a
Cronbach’s alpha of .806 for pre-test items, and
.911 for post-test items. In other words, these
items as together are a reliable measure of the
underlying concept of computational thinking.
o Change from pre-test to post-test was
computed as the mean arithmetical difference
(i.e., mean of all pre-test minus post-test
differences).

16. Computational Thinking – JPW students
In addition, students in journalism classes were asked “to what extent do you
agree or disagree with each of the following:” with response categories of:
Strongly Agree (coded 4), Agree (3), Disagree (2), or Strongly Disagree (1)
with the following items:
• I can conduct research and evaluate information by methods appropriate
to journalism.
• I can edit
Change from pre-test to post-test was computed as the mean arithmetical
difference (i.e., mean of all pre-test minus post-test differences). It should be
noted that an error in the electronic post-test made evaluation of the final
item impossible.
There were 31 valid cases for the valid item.
Reliability analysis of the one valid item above added to previous eight items
as a measure of computational thinking among JPW / IMM students is
indicated by a Cronbach’s alpha of .824 for pre-test items and .894 for post-
test items.

17. Computational Thinking – JPW students
In Fall 2014, an additional set of items were added for journalism
students, asking “to what extent do you agree or disagree with each of
the following:” with response categories of: Strongly Agree (coded 4),
Agree (3), Disagree (2), or Strongly Disagree (1) with the following items:
• I am motivated to learn new applications in computer technology on
my own that are relevant to careers in journalism
• I am motivated to learn new applications in computer technology with
my peers that are relevant to careers in journalism.
• I am motivated to take courses in computer science that are relevant to
careers in journalism.
• I am motivated to learn how computer technology is created for use in
journalism
Over the course of two semesters, we collected responses from 15
students on these four items.
Reliability analysis indicated a Cronbach’s alpha of .920 for pre-test items
and .968 for post-test items.

18. 18

19. 19

20. Students in Journalism/IMM classes:
Motivation to learn/pursue computational skills

21. Conclusions and future research
o Immersive, collaborative experiences do seem to
increase journalism students’ motivation to
pursue computing related to their field.
o Need to look at scaffolding and integration of
computational thinking throughout the
Journalism curriculum. OpenHTML may offer an
approach.
o May be an approach to combatting stereotype
threat and improving diversity in computational
journalism.
o More info: http://tardis.tcnj.edu/CABECT