K-8 Learning Trajectories Derived from Research Literature

Rich, Kathryn M.; Strickland, Carla; Binkowski, T.A.; Moran, Cheryl; Franklin, Diana

doi:10.1145/3105726.3106166

Cited by 98 publications

(21 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Introductory programming frequently begins with introducing basic operations such as conditionals (Rich et al, 2017). however, there are some longdocumented weaknesses that humans demonstrate when reasoning about conditionals.…”

Section: Examining Casesmentioning

confidence: 99%

Student Knowledge and Misconceptions

Lewis¹,

Clancy²,

Vahrenhold³

2019

The Cambridge Handbook of Computing Education Research

View full text Add to dashboard Cite

Section: Examining Casesmentioning

confidence: 99%

Student Knowledge and Misconceptions

Lewis¹,

Clancy²,

Vahrenhold³

2019

The Cambridge Handbook of Computing Education Research

View full text Add to dashboard Cite

“…This is possible due to increased empirical knowledge about this progression -a knowledge currently lacking in computer science education. One reason is that there are seldom efforts to collect and systematize about such progressions in a domain; Rich et al [9] is an example of such approach in K-6 education.…”

Section: Related Workmentioning

confidence: 99%

Program Comprehension

Izu

Schulte

Aggarwal

et al. 2019

Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education

View full text Add to dashboard Cite

This working group asserts that Program Comprehension (PC) plays a critical part in the writing process. For example, this abstract is written from a basic draft that we have edited and revised until it clearly presents our idea. Similarly, a program is written in an incremental manner, with each step being tested, debugged and extended until the program achieves its goal. Novice programmers should develop their program comprehension as they learn to code, so that they are able to read and reason about code while they are writing it. To foster such competencies our group has identified two main goals: (1) to collect and define learning activities that explicitly cover key components of program comprehension and (2) to define possible learning trajectories that will guide teachers using those learning activities in their CS0/CS1 or K-12 courses. We plan to achieve these goals as follows: Step 1-Review the current state of research and development by analyzing literature on classroom activities that improve program comprehension. Step 2-Concurrently, survey lecturers at various institutions on their use of workshop activities to foster PC.

show abstract

“…Graphs are often chosen for representing the curriculum because they match the structure of the curriculum which has courses and dependencies 8,9,10,11,12,13 . In graph-based representations of the curriculum, each course is represented by a vertex and each dependency is represented by an edge.…”

Section: Graph-based Representationsmentioning

confidence: 99%

“…Similar to the STOPS system, Siirtola et al used a graph-based representation to map courses and topics together they also show how these map to other courses 10 . Rich et al explored using graphs to represent dependencies between topics which could also inform curriculum design 12 . Based on their representation, material could be spaced out throughout the curriculum or throughout a course.…”

Section: Graph-based Representationsmentioning

confidence: 99%

“…Curriculum designers often have to adapt these recommendations to meet the many complex needs of their specific student population. Currently, there exist many tools for visualizing the content and sequence of a curriculum 8,9,10,11,12,13,14 . However, none of these tools help curriculum designers determine whether a given curriculum meets the needs of a specific student population.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Curri: A Curriculum Visualization System that Unifies Curricular Dependencies with Temporal Student Data

MacNeil¹,

Dorodchi²,

Al-Hossami³

et al.

2020 ASEE Virtual Annual Conference Content Access Proceedings

View full text Add to dashboard Cite

Stephen's research focuses on how people collaboratively make sense of complex, 'wicked' problems. Wicked problems are dynamic and constantly changing. They involve multiple stakeholders, often with conflicting requirements. To address these challenges, Stephen develops sociotechnical systems that collect, organize, and use data to support reflection and collective action. He received his Ph.D. at UNC in Charlotte and is currently a postdoctoral researcher in the Design Lab at UC San Diego.Dr. Mohsen M Dorodchi, UNC, Charlotte Dr. Dorodchi has been teaching in the field of computing for over 30 years of which 20 years as educator. He has taught majority of the courses in the computer science and engineering curriculum over the past 20 years such as introductory programming, data structures, databases, software engineering, system programming, etc. He is involved in multiple NSF supported research projects including Learning and Predictive Analytics Research, Research Practitioner Partnership, Implementing Teaching Methods to help Students learn more efficiently in active learning, etc.

show abstract

K-8 Learning Trajectories Derived from Research Literature

Cited by 98 publications

References 33 publications

Student Knowledge and Misconceptions

Student Knowledge and Misconceptions

Program Comprehension

Curri: A Curriculum Visualization System that Unifies Curricular Dependencies with Temporal Student Data

Contact Info

Product

Resources

About