An official website of the United States government
Creating pathways that stimulate high school learners’ interest in advanced topics with the goal of building a diverse, gender-balanced, future-ready workforce is crucial. To this end, we present the curriculum of a new, high school computer science course under development called Computer Science Frontiers (CSF). Building on the foundations set by the AP Computer Science Principles course, we seek to dramatically expand access, especially for high school girls, to the most exciting and emerging frontiers of computing, such as distributed computation, the internet of things (IoT), cybersecurity, and machine learning. The modular, open-access, hands-on curriculum provides an engaging introduction to these advanced topics in high school because currently they are accessible only to CS majors in college. It also focuses on other 21st century skills required to productively leverage computational methods and tools in virtually every profession. To address the dire gender disparity in computing, the curriculum was designed to engage female students by focusing on real world application domains, such as climate change and health, by including social applications and by emphasizing collaboration and teamwork. Our paper describes the design of curricular modules on Distributed Computing, IoT/Cybersecurity, and AI/Machine Learning. All project-based activities are designed to be collaborative, situated in contexts that are engaging to high school students, and often involve real-world world data. We piloted these modules in teacher PD workshops with 8 teachers from North Carolina, Tennessee, Massachusetts, Pennsylvania, and New York who then facilitated virtual summer camps with high school students in 2020 and 2021. Findings from teacher PD workshops as well as student camps indicate high levels of engagement in and enthusiasm for the curricular activities and topics. Post-intervention surveys suggest that these experiences generate student interest exploring these ideas further and connections to areas of interest to students.
more »
« less
Engaging Students in Exploring Computer Hardware Fundamentals Using FPGA Board Games.
Electronic devices have become indispensable in everyone’s life and so the computer hardware industry is demanding skilled professionals to design and physically implement devices to satisfy the market. However, misconceptions surrounding manufacturing jobs and the increasing initiatives to motivate students with engineering majors to focus on software-related topics such as artificial intelligence and blockchain are hindering students’ interest in hardware computing. Our project, funded by the NSF’s Improving Undergraduate STEM Education (IUSE) program, addresses the need to engage more students in explorations (and, eventually, design) of computer hardware by developing a set of games played on an easy-to-use hardware platform to understand and implement the fundamental concepts that are essential to modern computing systems (Figure 1). To encourage flexible and broad adoption, the games are conceived as standalone units within a curriculum design that leverages equitable pedagogical practices, experiential learning, and inquiry-based learning to cultivate engineering identity and persistence using situational interest and self-efficacy theories. We aim to offer the curriculum as an elective undergraduate course for all engineering majors at two US institutions and also research and evaluate the feasibility of implementing it as a summer program with high school students. Each module in the curriculum is divided into 5 phases: activation of prior knowledge, mini-lesson, gameplay, student-led work time, and debriefing. The games support collaboration rather than competition, and each lesson is tagged with equity spotlights, including Universal Design for Learning (UDL) and Culturally Sustaining Pedagogies (CSP) principles. Finally, informed by the Technological Pedagogical Content Knowledge (TPACK) framework, each lesson includes a teacher implementation guide and teacher educative materials to facilitate implementation (Figure 2). We have tested the first two games in the curriculum for usability and feasibility with a group of high school students. The topics of these games include binary arithmetic and Boolean logic gates. Participants were challenged to solve tasks using the hardware tools at their disposal. This usability and feasibility testing study provided us with important design and implementation implications.
more »
« less
- Award ID(s):
- 2142473
- PAR ID:
- 10488603
- Publisher / Repository:
- 2023 ASEE Annual Conference & Exposition
- Date Published:
- Journal Name:
- 2023 ASEE Annual Conference & Exposition
- Format(s):
- Medium: X
- Location:
- Baltimore, MD
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Preservice teachers (PSTs) in an educational foundations course were tasked with leading elementary students in an engineering design challenge. To explore different approaches for helping the PSTs develop competence in engineering education, two implementation methods were tested. In Spring 2022, PSTs collaborated with undergraduate engineering students to develop carnival-themed design challenge lessons. In Fall 2022, PSTs worked with their PST classmates to teach a professionally prepared engineering lesson focused on designing plastic filters. PSTs’ knowledge of engineering and engineering pedagogy were compared across the two semesters using an exploratory approach. Both groups showed increases in engineering knowledge and engineering pedagogical knowledge. Item-level differences suggest unique benefits to each approach providing insight for teacher educators designing interventions to prepare PSTs to integrate engineering into elementary education.more » « less
-
In recent years, Wyoming has developed Computer Science (CS) standards for adoption and use within K-12 classrooms. These standards, adopted in January of 2022, go into effect for the 2022-2023 school year. The University of Wyoming has offered two different computer science week-long professional developments for teachers. Many K-12 teachers do not have a CS background, so developing CS lessons plans can be a challenge in these PDs.This research study is centered around three central questions: 1) To what extent did K-12 teachers integrate computing topics into their PD created lesson plans; 2) How do the teacher perceptions from the two CS PDs compare to each other; and 3) How was the CS PD translated to classroom activity? The first PD opportunity (n=14), was designed to give hands-on learning with CS topics focused on cybersecurity. The second PD opportunity (n=28), focused on integrating CS into existing curricula. At the end of each of these PDs, teacher K-12 teachers incorporated CS topics into their selected existing lesson plan(s). Additionally, a support network was implemented to support excellence in CS education throughout the state. This research study team evaluated the lesson plans developed during each PD event, by using a rubric on each lesson plan. Researchers collected exit surveys from the teachers. Implementation metrics were also gathered, including, how long each lesson lasted, how many students were involved in the implementation, what grades the student belonged to, the basic demographics of the students, the type of course the lesson plan was housed in, if the K-12 teacher reached their intended purpose, what evidence the K-12 teacher had of the success of their lesson plan, data summaries based on supplied evidence, how the K-12 teachers would change the lesson, the challenges and successes they experienced, and samples of student work. Quantitative analysis was basic descriptive statistics. Findings, based on evaluation of 40+ lessons, taught to over 1500 K-12 students, indicate that when assessed on a three point rubric of struggling, emerging, or excellent - certain components (e.g., organization, objectives, integration, activities & assessment, questions, and catch) of K-12 teacher created lessons plans varied drastically. In particular, lesson plan organization, integration, and questions each had a significant number of submissions which were evaluated as "struggling" [45%, 46%, 41%] through interesting integration, objectives, activities & assessment, and catch all saw submissions which were evaluated as "excellent" [43%, 48%, 43%, 48%]. The relationship between existing K-12 policies and expectations surfaces within these results and in combination with other findings leads to implications for the translation of current research practices into pre-collegiate PDs.more » « less
-
Cybersecurity workforce development is the key to protecting information and information systems, and yet more than 30% of companies are short on security expertise. To address this need, the current authors have developed four cybersecurity education games to teach social engineering, secure online behavior, cyber defense methods, and cybersecurity first principles. These games are intended to recruit the next generation cybersecurity workforce by developing an innovative cybersecurity curriculum and pedagogical methods to provide high school students with hands-on activities in a game-based learning environment. Purdue University Northwest (PNW) offered high school summer camps for 181 high school students in June of 2016 and June of 2017. Out of 181 high school participants, 107 were underrepresented minority students, including African Americans, Hispanics, Asians, and Native Americans. To evaluate the effectiveness of the cybersecurity education games, post-camp surveys were conducted with 154 camp participants. The survey results indicated that the games were very effective in cybersecurity awareness training. Furthermore, the cybersecurity education games were more effective for male students than female students in raising student interest in computer science and cybersecurity.more » « less
-
Machine Learning in a Molecular Modeling Course for Chemistry, Biochemistry, and Biophysics Studentsnull (Ed.)ABSTRACT Recent advances in computer hardware and software, particularly the availability of machine learning (ML) libraries, allow the introduction of data-based topics such as ML into the biophysical curriculum for undergraduate and graduate levels. However, there are many practical challenges of teaching ML to advanced level students in biophysics majors, who often do not have a rich computational background. Aiming to overcome such challenges, we present an educational study, including the design of course topics, pedagogic tools, and assessments of student learning, to develop the new methodology to incorporate the basis of ML in an existing biophysical elective course and engage students in exercises to solve problems in an interdisciplinary field. In general, we observed that students had ample curiosity to learn and apply ML algorithms to predict molecular properties. Notably, feedback from the students suggests that care must be taken to ensure student preparations for understanding the data-driven concepts and fundamental coding aspects required for using ML algorithms. This work establishes a framework for future teaching approaches that unite ML and any existing course in the biophysical curriculum, while also pinpointing the critical challenges that educators and students will likely face.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Proceeding:
- The DOI is not currently available.
