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Empirical analysis of eye movements during code reading : evaluation and development of methods / by Teresa Busjahn. Paderborn, 2021
Inhalt
Introduction
Motivation
The importance of code reading and understanding
Code reading in computer science education
The nature of source code
Research questions
Structure of this work
Background
Why using gaze
The human eye and its movements
Recording eye movements
Eye movements in programming
EMCR study description
Synopsis
Study design
NT reading
SC reading
Novice programmers
Expert programmers
Participants
Novice programmers
Expert programmers
Detecting oculomotor events
Introduction
Choosing a suitable approach
Choosing an algorithm
Adapting the algorithm
Duration
Dispersion
Setting parameters
Duration
Dispersion
Event detection on the EMCR data
Comparing algorithm variants
Comparing parameter variants
Post-Processing
Conclusion
Eye tracking error
Introduction
Data quality
Accuracy, precision, valid samples
Error sources
Factors concerning the recording system and environment
Factors concerning the participant
Conclusion
Existing approaches for addressing error
Error debilitation and data removal
Stimulus preparation
Recalibration
Removing problematic data
Error correction
Source-centric methods
Data-centric methods
Manual correction
Automatic correction
General-purpose approaches
Task-specific approaches for (code) reading
Conclusion
Evaluation approaches for error correction
Real data
Comparison with manual correction
Reference locations
Visualizations
Comparison with another correction method
Further measures
Artificial data
Conclusion
Conclusion
Error correction
Introduction
Correction approaches
Nüssli 2011
Lohmeier 2015
Novel approach
Error function
Finding parameters
Adapting AOIs
Variants for evaluation
Evaluation using reference locations
Stimuli
Text
Grid
Recording situation and participants
Analysis procedure and results
Reference locations
Errors
Correction
Chosen approaches
Conclusion
Evaluation using manually corrected data
Data
Analysis procedure and results
Plausibility check
Conclusion
Evaluation using artificial data
Data
Analysis procedure and results
Conclusion
Analysis procedure
Overview
Areas of interest
Preparation of data for statistical analysis
Comprehension questions
Event detection
Error correction
AOI sequences
Analysis measures
Introduction
Model behaviors
Single-event-based measures
Fixation duration
Number of fixations
Saccadic amplitude
AOI coverage
First visit to main
Event-sequence-based measures
Reading direction
Model occurrence and model similarity
Sequence alignment
Types of pairwise alignments
Adaption for EMCR data
Trial-based measures
Trial duration
Correctness of comprehension question
Summary of analyses measures
Analysis results
Introduction
Single-event-based measures
Fixation duration
Number of fixations
Saccadic amplitude
AOI coverage
First visit to main
Event-sequence-based measures
Reading direction
Model occurrence and model similarity
Trial-based measures
Trial duration
Correctness of comprehension question
Threats to validity
Conclusion
Synopsis
Natural-language text reading
Research question 1
Research question 2
Reflection on methods and analysis measures
Discussion and future work
Bibliography
List of figures
List of tables
List of abbreviations
Appendix
Questionnaires
Novices
Experts
Natural-language stimuli
NT1
NT2
NT3
Source code stimuli
Novices
L1_SC1
L1_SC2
L1_SC3
L3_SC1
L5_SC3
Experts
SC1
SC2
SC3
Expert interviews
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