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Motivating STEM+C Learning With Social Impact of Cybersecurity and Digital Forensics

Listen and learn

Listen and learn : Research paper
Lecture presentation


Friday, December 4, 12:45–1:30 pm PST (Pacific Standard Time)
Presentation 1 of 3
Other presentations:
Promoting Math Teachers’ Confidence and Self-Perceptions of Efficacy with Educational Technology
Integrating Science, Computational Thinking, and Data Science for Middle School Science Classrooms

Dr. Eoghan Casey  
Karen Peterson  
Daryl Pfeif  

This work demonstrates how cybersecurity and digital forensics are used to teach STEM+C in a multidisciplinary context, encompassing social issues, including justice, safety, privacy and ethics. Engaging students in virtualized problem-based investigations motivates them to learn scientific knowledge and technical skills from multiple perspectives and consider related careers.

Audience: Curriculum/district specialists, Principals/head teachers, Technology coordinators/facilitators
Attendee devices: Devices useful
Attendee device specification: Laptop: Mac, PC
Topic: Instructional design & delivery
Grade level: 9-12
Subject area: Career and technical education, STEM/STEAM
ISTE Standards: For Educators:
Facilitator
  • Manage the use of technology and student learning strategies in digital platforms, virtual environments, hands-on makerspaces or in the field.
For Students:
Digital Citizen
  • Students engage in positive, safe, legal and ethical behavior when using technology, including social interactions online or when using networked devices.
Computational Thinker
  • Students collect data or identify relevant data sets, use digital tools to analyze them, and represent data in various ways to facilitate problem-solving and decision-making.

Proposal summary

Framework

This work combines a sophisticated virtual learning environment hosted in the cloud with rich investigative scenarios with supporting educational resources to fuel in-classroom instructional activities and career pathway exploration. This program was designed and developed using an inquiry-based learning pedagogical framework, constructed around goal-based scenarios, cognitive apprenticeship, and collaborative peer learning, implementing a case-based instruction approach suitable for investigative domains (Bell, 1998; Bell, 1996a). Research shows we learn best through a combination of theory and practice in a realistic context (Brown, et. al. 1989). Theory is inert until it is applied to a realistic situation, and practice is shallow without the influence of theory (Norman, 1993). Students are motivated by goal accomplishment, including intrinsic satisfaction of solving a case, and earning merit for acquiring skills (Schank et. al. 1994). Careful attention is required to choose and structure multiple case scenarios in a way that helps students arrange them in their minds, make generalizations, and understand important aspects (Kolodner, 1994, Schank, 1977, Schank, 1990; Schank, 1994). Investigative scenarios in the Cyber Sleuth Science Lab cover issues that are directly relevant to students’ lives, including cyberbullying, privacy, identity theft, anonymous harassment, and unauthorized sharing of personal photographs. The virtual learning environment immerses students in the culture and practice of cybersecurity and digital forensics by providing access to professional software tools and realistic investigative challenges to solve. The investigative scenarios involve technology students use personally, and give youth more reasons to care about learning inquiry-based science and technology subjects, as well as computer science. In the words of the pioneers in situated cognition, we learn best when we learn “to use the tools as practitioners use them” (Brown et. al. 1989). Classroom activities provide additional support and role model engagement.

Methods

Research methods used include analysis of survey data from students and educators, analysis of qualitative data from focus groups during the project, and quantitative analysis of automatically generated back end metrics within the virtual learning environment, i.e., data analytics resulting from the students clicking through the interface and interacting with the system. Such detailed data about student progress and performance through each module and component within learning environment support measurement of effectiveness students in different context and circumstances. This click data shows the path a student took through an investigative scenario, the amount of support they required, and their unique challenges and successes. This quantitative data provides the foundation for addressing all of the research questions in this project. This quantitative data will be triangulated with other data sources, including survey results and focus groups. This combination of analysis methods increases the strength of study, providing context and background to help interpret the results. In addition, any inconsistencies between the results of different approaches will give rise to additional inquiry and analysis.

Results

All data has been gathered from pilots in multiple educational settings, and analysis will be completed by the end of 2019. Initial findings indicate that young women, and other traditionally underserved youth, are motivated to learn scientific and technical knowledge and skills, and pursue educational or career pathways related to STEM+C, when learning in a multidisciplinary context, encompassing social issues such as justice, safety, privacy and ethics. In addition, the analysis of gathered data could provide insights into learning processes and performance, including comprehension difficulties, confusion about user-interface, effectiveness of expert advice and supporting instructional modules, and successful outcomes.

Importance

This study demonstrates and evaluates an innovative implementation of learning science to teach STEM+C in an engaging way from multiple viewpoints, including social issues such as justice, safety, privacy and ethics. This work helps address the major shortage of qualified job candidates in Cybersecurity and Digital Forensics (traditionally underserved youth are underrepresented in these careers).

References

Ashcraft, C., Eger, E., Friend, M. (2012). Girls in IT: The facts. National Center for Women & Information Technology. Retrieved from: http://www.ncwit.org/sites/default/files/resources/girlsinit_thefacts_fullreport2012.pdf

Bell, B. L. (1998). Investigate and Decide Learning Environments: Specializing Task Models for Authoring Tool Design. The Journal of Learning Sciences, 7, 65-105

Bell, B. L. (1996a). A special-purpose architecture for the design of educational software (Tech. Rep. No. 70). Evanston, IL: Northwestern University, The Institute for the Learning Sciences.

Brown, J. S., Collins, A., and Duguid, P. (1989). Situated Cognition and the Culture of Learning. Educational Researcher, 18, 32-42.

Collins, A., J. S. Brown, and S. E. Newman (1989). Cognitive Apprenticeship: Teaching the Crafts of Reading Writing and Mathematics, In L. B. Resnick (Ed.), Knowing, learning, and instruction: Essays in honor of Robert Glaser, ed. L. Resnick, 140-185. Hillsdale, NJ: Lawrence Erlbaum Associates.

Denner, J. & Campe, S. (2018). Equity and inclusion in computer science education. In S. Sentence (Ed.), Computer Science Education in School: Perspectives on Teaching and Learning, pp. 189-206. UK: Bloomsbury

Kolodner, J. (1994). From Natural Language Understanding to Case-Based Reasoning and Beyond: A Perspective on the Cognitive Model That Ties It All Together. In R. C. Schank (Ed.), Beliefs, Reasoning and Decision Making, 55-110. Hillsdale, NJ: Lawrence Erlbaum Associates.

Modi, K., Schoenberg, J. Salmond, K. (2012). Generation STEM: What girls say about science, technology, engineering, and math. New York, NY: Girl Scouts of the USA.
Norman, Donald. (1993). Things that make us Smart. Addison-Wesley.

Schank, R. C., Fano, A., Bell, B, Jona, M. (1994). The Design of Goal-Based Scenarios. The Journal of Learning Sciences, 3, 305–345.

Schank, R. C. (1994). Goal-Based Scenarios: A radical look at education. The Journal of Learning Sciences, 3, 429–453.

Schank, R. C. (1994). Goal-Based Scenarios. In R. C. Schank (Ed.), Beliefs, Reasoning and Decision Making, 55-110. Hillsdale, NJ: Lawrence Erlbaum Associates.

Schank, R. C., Abelson, R. (1977). Scripts, Plans, Goals and Understanding. Hillsdale, NJ: Lawrence Erlbaum Associates.

Schank, R. C. (1990). Tell me a Story: Narrative and Intelligence. Evanston, IL: Northwestern University Press.

Wolff, J. (2015). Hackathons Have a Gender Problem: And they might explain why it’s so difficult to attract women to work in cybersecurity. FutureTense/Slate/ New America/ASU
Retrieved from:
http://www.slate.com/articles/technology/future_tense/2015/11/why_don_t_more_women_work_in_cybersecurity.html

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Presenters

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Dr. Eoghan Casey, Digital Forensics Solutions
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Karen Peterson, National Girls Collaborative

Karen A. Peterson is the Founder & Chief Executive Officer for the National Girls Collaborative. She has over 25 years of experience in education as a classroom teacher, university instructor, teacher educator, and researcher. NGCP seeks to maximize access to shared resources for public and private sector organizations interested in expanding girls’ participation in STEM. The overarching goal of the NGCP is to use the leverage of a network to create the tipping point for gender equity in STEM. Currently, NGCP serves 41 states, facilitating collaboration between organizations serving 20.15 million girls and 9.5 million boys.

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