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Collaborating Across Boundaries to Engage Journalism Students in Computational Thinking

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Presentation for #AEJMC15 Scholar to Scholar session, August 8, 2015

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Collaborating Across Boundaries to Engage Journalism Students in Computational Thinking

  1. 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. 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. 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. 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. 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. 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. 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. 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. 9. Finding our own “ghost factories” 9
  10. 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. 11 Work in progress handed off from semester to semester eg: customizable twitter tool, blogging module, legislation module.
  12. 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. 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. 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. 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. 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. 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.
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  20. 20. Students in Journalism/IMM classes: Motivation to learn/pursue computational skills
  21. 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

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