Developing Computational Thinking Skills Through Technological Invention

• In Event: Educational Responsibilities in Problem-Based Education (PBE): Principles, Practices, and Networks Creating and Supporting PBE

Abstract

Objective
This study examined the teaching of computer science (CS) and computational thinking (CT) principles and practices through a transdisciplinary approach to problem finding and solving known as invention education (Invention Education Research Group, 2019; Couch, et al., 2018). We explored: 1) how students engaged in computing practices while inventing, and 2) what CS/CT concepts and practices were acquired as students created a working prototype of their technological solution to a problem.

Conceptual Framework
This study was guided by constructionism (Harel & Papert, 1991), an epistemology that interprets how students build knowledge structures through what is being constructed (Estabrooks & Couch, 2018) in problem-based learning environments (Chan & Blikstein, 2018), including the creation of computational artifacts (Brennan & Resnick, 2012). The study is part of a larger study investigating the social and cultural aspects of learning while inventing (Couch et al., 2019; Kelly & Green, 2018; Green et al., 2012).

Modes of inquiry
Participants were selected from 173 high school students engaged in a nine-month team-based invention project in the 2018–2019 school year through InvenTeams, a national initiative administered by the Lemelson-MIT (LMIT) Program since 2004. Survey data for 96 students was supplemented by in-depth analysis of a purposeful sample of 12 students and 4 teachers from three teams whose projects could be categorized as part of the ‘Internet of Things’. Using holistic coding (Saldana, 2016), we analyzed posters, reports, presentations and transcripts of one-hour semi-structured interviews of 4 students from each team. We then compared the data to the core CS concepts and practices set forth in the 2016 K–12 Framework for Computer Science Education.

Data sources
Data included LMIT purchasing records of technology for 12 years, 2018 end of year surveys (n=96), and 3 teams’ descriptions of their prototypes, annotated code, invention statements, blog posts for 2018-19, end of year presentations, invention notebooks, summative reports, high school transcripts for 12 students, and transcripts of semi-structed interviews for twelve students and three teachers.

Results
2018 students’ (n=96) self-rankings of skill levels before and after the InvenTeam year increased in the ‘developing’ and ‘expert’ categories (versus novice or below novice) with respect to their use of 8 technologies, including microprocessors, solid modeling software, and scripting languages. The most reported resources for learning were YouTube (23%), teachers (20%), and trial-and-error (18%). Students described CS/CT as just another tool they needed to realize their invention ideas and found it difficult to distinguish between CS/CT learning and the invention process. In-depth examination of three teams provided evidence of learning of four out of five CS concepts and all seven CS practices recommended in the K12 Framework for Computer Science Education.

Scholarly significance
This study demonstrates that students can learn CS/CT principles and practices (Gershenfeld, 2008) while engaging in invention projects that address problems of significance. It also demonstrates an approach for investigating how knowledge in a singular discipline develops as learners, in the era of convergence, tackle problems at the interfaces of multiple fields and disciplines (NRC, 2014).

Authors

• Leigh Estabrooks, Massachusetts Institute of Technology

• Helen Zhang, Boston College

• Anthony M Perry, Massachusetts Institute of Technology

• Stephanie Renee Couch, Masschusetts Institute of Technology

• An-Me Chung, CSforALL