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An Experimental Method for the Active Learning of Greedy Algorithms
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1006/jvlc.2002.0239openalex-snapshot
ANIMAL: A System for Supporting Multiple Roles in Algorithm Animation
inferredcites →https://doi.org/10.1007/978-0-85729-443-2openalex-snapshot
Guide to Teaching Computer Science: An Activity-Based Approach
inferredcites →https://doi.org/10.1016/j.entcs.2008.12.059openalex-snapshot
PathFinder: A Visualization eMathTeacher for Actively Learning Dijkstra's Algorithm
inferredcites →https://doi.org/10.1076/csed.13.2.137.14200openalex-snapshot
Learning and Teaching Programming: A Review and Discussion
inferredcites →https://doi.org/10.1097/00006199-196807000-00014openalex-snapshot
The Discovery of Grounded Theory; Strategies for Qualitative Research
inferredcites →https://doi.org/10.1109/eurocon.2011.5929294openalex-snapshot
Experimentation with optimization problems in algorithm courses
inferredcites →https://doi.org/10.1109/icalt.2012.121openalex-snapshot
Observations as a Method to Evaluate a Computer-Based Approach to Learning Algorithms
inferredcites →https://doi.org/10.1109/mcg.2005.110openalex-snapshot
JHAVÉ: Supporting Algorithm Visualization
inferredcites →https://doi.org/10.1109/tlt.2009.36openalex-snapshot
Layered Architecture for Automatic Generation of Conflictive Animations in Programming Education
inferredcites →https://doi.org/10.1109/tlt.2013.8openalex-snapshot
GreedEx: A Visualization Tool for Experimentation and Discovery Learning of Greedy Algorithms
inferredcites →https://doi.org/10.1145/1028174.971312openalex-snapshot
Using software testing to move students from trial-and-error to reflection-in-action
inferredcites →https://doi.org/10.1145/1089786.1089790openalex-snapshot
Students' alternative standards for correctness
inferredcites →https://doi.org/10.1145/1189136.1189165openalex-snapshot
On the role of proofs in a course on design and analysis of algorithms
inferredcites →https://doi.org/10.1145/1268784.1268869openalex-snapshot
Fully integrating algorithm visualization into a cs2 course.
inferredcites →https://doi.org/10.1145/1352135.1352148openalex-snapshot
Learning from wrong and creative algorithm design
inferredcites →https://doi.org/10.1145/1538234.1538236openalex-snapshot
A Survey of Successful Evaluations of Program Visualization and Algorithm Animation Systems
inferredcites →https://doi.org/10.1145/1562877.1562917openalex-snapshot
Active learning of greedy algorithms by means of interactive experimentation
inferredcites →https://doi.org/10.1145/1584322.1584330openalex-snapshot
Commonsense computing (episode 5)
inferredcites →https://doi.org/10.1145/1999747.1999753openalex-snapshot
The design and coding of greedy algorithms revisited
inferredcites →https://doi.org/10.1145/2325296.2325311openalex-snapshot
Refinement of an experimental approach tocomputer-based, active learning of greedy algorithms
inferredcites →https://doi.org/10.1145/299649.299747openalex-snapshot
Do we teach the right algorithm design techniques?
inferredcites →https://doi.org/10.1145/330908.331802openalex-snapshot
Design and analysis of algorithms reconsidered
inferredcites →https://doi.org/10.1145/611892.611920openalex-snapshot
The greedy trap and learning from mistakes
inferredcites →https://doi.org/10.1145/960492.960540openalex-snapshot
Evaluating the educational impact of visualization
inferredcites →https://doi.org/10.1145/971300.971312openalex-snapshot
Using software testing to move students from trial-and-error to reflection-in-action
inferredcites →https://doi.org/10.1201/9781482287325openalex-snapshot
Computer Science Education Research
inferredcites →https://doi.org/10.1201/9781482287325-19openalex-snapshot
Critical Enquiry in CS Education
inferredcites →https://doi.org/10.15388/infedu.2004.19openalex-snapshot
Visual Algorithm Simulation Exercise System with Automatic Assessment: TRAKLA2
inferredcites →https://doi.org/10.1590/0104-4060.52442openalex-snapshot
Becoming Critical: education, knowledge and action research
inferredcites →https://doi.org/10.2307/1495177openalex-snapshot
Becoming Critical: Education, Knowledge, and Action Research
inferredcites →https://doi.org/10.2307/2575405openalex-snapshot
The Discovery of Grounded Theory: Strategies for Qualitative Research.
inferredcites →https://doi.org/10.4324/9780203017548openalex-snapshot
Computer Science Education Research
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/cae.21655openalex-snapshot
GreedExCol, A CSCL tool for experimenting with greedy algorithms
inferred← citeshttps://doi.org/10.1002/cae.22023openalex-snapshot
The GreedEx experience: Evolution of different versions for the learning of greedy algorithms
inferred← citeshttps://doi.org/10.1007/978-3-319-22900-3_4openalex-snapshot
Design and Evaluation of OptimEx, an Experimentation System for Optimization Algorithms
inferred← citeshttps://doi.org/10.1007/978-3-662-63214-7_15openalex-snapshot
Unterschiede im Leseverhalten von Algorithmen und Programmen
inferred← citeshttps://doi.org/10.1109/educon.2017.7943057openalex-snapshot
Exploring the joint use of educational theories and information technology to improve CS courses
inferred← citeshttps://doi.org/10.1109/educon45650.2020.9125179openalex-snapshot
Addressing Students’ Creativity in Algorithm Design
inferred← citeshttps://doi.org/10.1109/educon46332.2021.9453904openalex-snapshot
Students’ Emotions Using an Algorithm Experimentation Tool in the New Normal
inferred← citeshttps://doi.org/10.1109/fie44824.2020.9273920openalex-snapshot
Using Large-Scale Optimality Testing as a Tool for Analysis Tasks in Algorithm Courses
inferred← citeshttps://doi.org/10.1109/icpc52881.2021.00053openalex-snapshot
Is Algorithm Comprehension Different from Program Comprehension?
inferred← citeshttps://doi.org/10.1109/rev.2016.7444481openalex-snapshot
"Virtual" experimentation on algorithm optimality
inferred← citeshttps://doi.org/10.1109/rita.2016.2589620openalex-snapshot
Evaluation Experiences of the Representation Techniques of Greedy Programs: Application to the GreedEx Tool
inferred← citeshttps://doi.org/10.1109/siie.2014.7017698openalex-snapshot
Difficulties, attitudes and misconceptions on experimenting with optimization algorithms
inferred← citeshttps://doi.org/10.1109/siie.2017.8259642openalex-snapshot
OptimEx2: Enhancing an experimentation system targeted at optimization algorithms
inferred← citeshttps://doi.org/10.1109/siie48397.2019.8970134openalex-snapshot
Extending Instructional Support in an Algorithm Benchmarking System
inferred← citeshttps://doi.org/10.1109/t4e.2015.26openalex-snapshot
GATutor: A Guided Discovery Based Tutor for Designing Greedy Algorithm
inferred← citeshttps://doi.org/10.1145/3304221.3319749openalex-snapshot
Students' Misconceptions of Optimization Algorithms
inferred← citeshttps://doi.org/10.1145/3564721.3564739openalex-snapshot
Improving Interactive Instruction: Faculty Engagement Requires Starting Small and Telling All
inferred← citeshttps://doi.org/10.1145/3641554.3701937openalex-snapshot
Reflections on Teaching Algorithm Courses
inferred← citeshttps://doi.org/10.1145/3641554.3701968openalex-snapshot
Mathematical Underpinnings of Algorithms via In-class Activities
inferred← citeshttps://doi.org/10.1145/3689187.3709612openalex-snapshot
What We Talk About When We Talk About K-12 Computing Education
inferred← citeshttps://doi.org/10.1145/3727987openalex-snapshot
Teaching Algorithm Design: A Literature Review
inferred← citeshttps://doi.org/10.1145/3786228.3786240openalex-snapshot
How do Students Select an Algorithm Design Technique?
inferred← citeshttps://doi.org/10.4018/978-1-4666-7304-5.ch004openalex-snapshot
A Review of Teaching and Learning through Practice of Optimization Algorithms
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