PATHFINDER

Welcome to my Research Pathfinder. As I undertake my Doctoral Studies (Ed.D.) in the Learning Sciences, this pathfinder will continue to form the base for a curated set of research artifacts, including key personnel, scholarly sources and web-based multimedia. I hope you enjoy this learning journey with me.

- Sue Mylde, June 2024.

RESEARCH & LEARNING SCIENCES CONNECTIONS

As a first-year scholar, I am casting a wide net for my research area with the full awareness that as my doctorate progresses, I will have to narrow my work to focus on a research question. I have identified three topics of interest: Computer Science, Robotics and Artificial Intelligence (AI). While these topics may seem somewhat disparate, they are strongly connected to the role that I serve at my school as the Innovation, Design, Entrepreneurship and Skills (IDEAS) Co-ordinator (as mentioned in the Researcher tab).

Herein I identify some perspectives and questions I am interested in within Computer Science and Artificial Intelligence. These topics have received most of my focus right now due to the progress of my work for this term so far as I've been making Learning Sciences connections to my topic through readings of Sawyer (2022) and Hoadley (2018) and other relevant scholars.

I find myself drawn to teacher-support and teacher education to better support technoscience education in the K-12 learning contexts. As such my scholarly discussion papers during my first year will examine the topics for CS and AI from the teacher perspective.

Computer Science

Pedagogical Approaches & Curriculum Development:

How do different teaching methodologies (e.g., project-based, problem-based, inquiry-based) impact students' understanding of computational concepts and problem-solving skills?
What role does active learning play in promoting deep understanding and retention of computer science concepts among students from diverse backgrounds?
How can we effectively integrate computational thinking into other subject areas to enhance student learning across disciplines?
How best to deploy curriculum for this ever-evolving subject? Can a written curriculum cope with CS development?

Educator/ Teacher / Coach role:

What role does teacher confidence and efficacy play in developing Computer Science competencies in students (K-12)?
How can teacher/educator training impact CS delivery in schools?

Student Learning and Cognition:

What are the common misconceptions and difficulties students encounter when learning to program, and how can these be addressed through instructional interventions?
How does prior knowledge in mathematics and problem-solving influence students' success in learning computer science?
What role does motivation and self-efficacy play in students' persistence and achievement in computer science?

Assessment and Evaluation:

How can we develop valid and reliable assessment methods to measure students' computational thinking skills and problem-solving abilities?
What are the strengths and limitations of different assessment formats (e.g., traditional exams, portfolios, projects) for evaluating computer science learning?
How can formative assessment be used to inform instruction and improve student learning outcomes in computer science?

Artificial Intelligence

AI for Enhancing Teaching and Learning Teacher Support:

How can AI-powered tools be designed to support teachers in planning, delivering, and assessing instruction?
What are the challenges and opportunities for using AI to provide personalized professional development for teachers?
How can AI be used to facilitate collaboration and knowledge sharing among teachers?

AI & Ethics

How can AI systems in education be developed and deployed in ways that minimize bias and ensure fairness for all students?
What are the potential consequences of algorithmic bias in AI-driven educational systems?
How can educators and policymakers address ethical concerns related to AI in education?
What are the ethical implications of using AI in education? How can we ensure fairness, transparency, and unbiased learning experiences for all students?

AI & the Learning Environment:

How can AI be used to increase student engagement and motivation in learning?
Can AI-powered games or simulations effectively promote deeper understanding of concepts?
Teacher Roles: How will AI transform the role of teachers? Will AI replace teachers or become valuable collaborators, allowing teachers to focus on more complex tasks like personalized instruction and social-emotional learning?

References

Hoadley, C. (2018). A short history of the Learning Sciences. In Fischer, F., Hmelo-Silver, C. E., Goldman, S. R., & Reimann, P. (Eds.) (pp. 11-23). (2018). International handbook of the learning sciences. Routledge. https://doi-org.ezproxy.lib.ucalgary.ca/10.4324/9781315617572

Sawyer, R. K. (Ed.) (2022). The Cambridge handbook of the learning sciences. (3rd ed.) Cambridge University Press.

Interdisciplinary

"The learning sciences (LS) is an interdisciplinary field." LS researchers and practitioners need to collaborate across disciplines to understand the many different ways to think about learning. Sawyer (2022, p. 1)

Instructionism

“The traditional vision of schooling is known as instructionism (Papert, 1993). Instructionism prepared students for the industrialized economy of the early 20th century.” (Sawyer, 2022, p, 2)

Logical Empiricism

“In the first half of the 20th century, philosophers came to a consensus on the nature of scientific knowledge: scientific knowledge consisted of statements about the world and of logical operations that could be applied to those statements. This consensus was known as logical empiricism (McGuire, 1992; Suppe, 1974). Logical empiricism combined with behaviourism and traditional classroom practice to form the instructionist approach to education: disciplinary knowledge consisted of facts and procedures, and teaching was thought of as transmitting the facts and procedures to students.” (Sawyer, 2022, p. 7)

Situativity

“Situativity means that knowledge is not just a static mental structure inside the learner’s head; instead, knowing is a process that involves the person, the tools and other people in the environment, and the activities in which that knowledge is being applied. The situativity perspective moves us beyond a transmission and acquisition conception of learning; in addition to acquiring content, what happens during learning is that patterns of participation in collaborative activity change over time (Rogoff, 1990, 1998)” (in Sawyer, 2022, p. 6)

Constructivism

Influential theory in learning sciences. Originated by Jean Piaget. "Constructivism posits that learning involves the active creation of mental structures, rather than passive internalisation of information acquired from others or from the environment." (Nathan & Sawyer, 2022, p. 31)

Constructionism

A learning theory concept developed by Seymour Papert (1928-2016), building upon Piaget's constructivism. That knowledge can be built by the learner through the active creation of something else that is shareable, e.g. a poem, program or other item (Stager, 2016)

Computer-Supported Collaborative Learning

CSCL is "an innovative conceptualization and implementation of learning and thinking" (Stahl et. al., 2022, p.407). It is a multifaceted effort that integrates theory, pedagogy, methodology and technology.

Sociocultural Theory

Intelligent behaviour occurs within complex social and physical environments "filled with tools and machines, discipline-specific systems of notation, and other social agents... learning occurs in environments that are collaborative and technologically rich." Sociocultural theory has been very influential to how learning sciences can be understood - collaboration being a key part of social dynamics in learning environments. (Nathan & Sawyer, 2022, p. 32)

AI Literacy

"AI literacy is the ability to readily engage with AI by leveraging AI tools, systems and frameworks to effectively and ethically solve problems in a wide range of sociocultural contexts." (Wang & Lester, 2023)

more soon

References

Nathan, M. J. & Sawyer, R. K. (2022). Foundations of the learning sciences. In R. K. Sawyer (Ed.), The Cambridge handbook of the learning sciences (3rd ed., pp. 27-52). Cambridge University Press.

Sawyer, R. K. (2022). An introduction to the learning sciences. In R. K. Sawyer (Ed.), The Cambridge handbook of the learning sciences (3rd ed., pp. 1-23). Cambridge University Press. https://doi-org.ezproxy.lib.ucalgary.ca/10.1017/CBO9781139519526

Stager, G. Seymour Papert (1928–2016). Nature 537, 308 (2016). https://doi.org/10.1038/537308a

Stahl, G., Koschmann, T., & Suthers, D. (2022). Computer-Supported Collaborative Learning. In R. K. Sawyer (Ed.), The Cambridge Handbook of the Learning Sciences (3rd ed., pp. 479–496). Cambridge University Press. https://doi-org.ezproxy.lib.ucalgary.ca/10.1017/CBO978113951952

Wang, N., & Lester, J. (2023). K-12 Education in the Age of AI: A Call to Action for K-12 AI Literacy. International Journal of Artificial Intelligence in Education, 33(2), 228–232. https://doi.org/10.1007/s40593-023-00358-x

PURPOSE

As a learner, learning designer and educator, I have always been drawn to organization and clarity. As I embark on this scholarly journey into research in pursuit of a Doctor of Education (Ed.D.) degree, I have found a pressing need not just for a structure to help me organize my resources, but also for coherence and precision. The idea of a pathfinder seems appropriate not only to categorize the key resources I have found as my research progresses but also perhaps more importantly, a way to lead me and others to different parts of my research.

Structure of my pathfinder

Broadly, I have started to organise the Wakelet Collection into different sections (e.g. Journals, Research Topics, Research Personnel) to provide me with a starting point for my pathfinder.

Within each section, resources are organised meaningfully, for example, ‘Watch’, ‘Listen’, ‘Read’, and ‘Engage’ to identify the different action-oriented ways to connect with the collected materials.

Wakelet & Substack

Under the Resources tab above, you will find two links for my ‘Curated Resources’ and ‘Written Word’.

Curated Resources will take you to the abovementioned Wakelet collection. I chose the Wakelet tool for its overall versatility in organizing resources. I also am a fan of how I can personalise these pages without too much coding/programming work. This tool is fit for purpose in my view.

I decided to start a Substack, called ‘EngagEd’ to help with my writing work. It is an easy to use interface and allows me to self-publish a blog-like collection of articles. I was intrigued by Wendy Belcher’s notion of “I get to write today”. I believe this substack will help me hone my writing skills as I write on the research topics of interest to me, as well as on the work of being a scholar.

RESEARCHER

“There are three Things extreamly [sic] hard, Steel, a Diamond and to know one’s self.”

- Benjamin Franklin (Founders Online: Poor Richard Improved, 1750).

I serve in two roles at my school (Rundle College) in Calgary, Alberta. First, I teach Computer Science to Junior and Senior High (Grades 7-12) students. I have taught Computer Science for three years, developing and teaching the curriculum for this program since September 2021. Second, I serve in a leadership role within IDEAS where I coordinate initiatives for Innovation, Design, Entrepreneurship and Skills (IDEAS). I have served in this latter role for about one year, focusing on the strategic alignment of the Computer Science and Robotics program for K-12 at all six schools/divisions within the organisation (including Rundle College, Rundle Academy and Rundle Studio) as well as the strategic guidance and deployment for Artificial Intelligence teaching and learning across the organisation.

I am fortunate that my work aligns closely with my passion for technoscience education, defined by Kayumova and Sengupta (2023, p. 218) as “education at the intersection of science, technology, computing, and engineering disciplines”. I have worked closely with students, teachers (both at and outside of my school), as well as administration as my role allows me to consider the whole learning environment. I align strongly with Sawyer’s definition of the learning environment (2022, p.9) as including “the people in the environment (teachers, learners, parents, peers, and others); the computers in the environment and the roles they play; the architecture and layout of the room and the physical objects in it; and the social and cultural environment.” My role has enabled me to ask both systemic as well as more elemental questions about the learning environments where I operate.

I have chosen the three topics of research, namely Computer Science, Robotics and Artificial Intelligence as I am excited about many different aspects of each of these topics. I am early enough in my research that I have not honed specifically on one topic, but I will highlight a few areas of interest so far, in the Research tab above.

Notably, this question ‘How can we make a difference in our world?’ is a provocation I have continued to use in my Computer Science classroom. While it is my way of reminding my students to remember there is a big picture context that their work will serve (beyond creating a game for self-entertainment - which is a popular impression that many have about Coding/Programming), I also am drawn to the reflection that this question demands both from myself and my students. As I situate myself within my research, I want my work to be driven by purposeful, and meaningful impact - to make a difference in our world.

References

Founders Online: Poor Richard Improved, 1750. (n.d.). University of Virginia Press. Retrieved July 17, 2024, from http://founders.archives.gov/documents/Franklin/01-03-02-0176

Kayumova, S. & Sengupta, P. (2023). Beyond representationalism: Heterogeneity as an ethical turn in STEM and computing education. In Shanahan, M. C., Beaumie, K., Takeuchi, M. A., Koh, K., Preciado-Babb, A. P., & Sengupta, P. (Eds.), The learning sciences in conversation: Theories, methodologies, and boundary spaces (pp. 218-234). Routledge. https://doi.org/10.4324/9781003089728-25

Sawyer, R. K. (2022). Introduction: The new science of learning. In R. K. Sawyer (Ed.), The Cambridge handbook of the Learning Sciences (3rd ed., pp. 1–23). Cambridge University Press. https://doi.org/10.1017/CBO9781139519526.002

RESOURCES

Curated Resources

Written Word

To organize this pathfinder of resources and my own written work, I have linked these separately above. These links will take you off this site.

Curated Resources will take you to my Wakelet collection of resources. I found this Wakelet tool ideal for categorising and organising the bulk of the resources I believe will be helpful for the research work ahead.

Written Word will take you to EngagEd, the Substack I have started to use for my writing. Please feel free to click on 'No Thanks' without subscribing to go straight to the content. Substack defaults to this subscription landing page if you are accessing the substack for the first time. My apologies for this inconvenience.