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Julian Fernald

dblp:07/4298 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2003
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1Human-computer interaction and ubiquitous computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Computing education · 100%
Software engineering, system software, and programming languages
1 paper
Empirical software engineering · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computing education › collaborative learning
pair programming
0.012003
The Impact of Pair Programming on Student Performance, Perception and Persistence · ICSE 2003
Empirical software engineering
developer studies
0.012003
The Impact of Pair Programming on Student Performance, Perception and Persistence · ICSE 2003
YearPublicationVenuePosition
2003 The Impact of Pair Programming on Student Performance, Perception and Persistence
abstract
This study examined the effectiveness of pair programming in four lecture sections of a large introductory programming course. We were particularly interested in assessing how the use of pair programming affects student performance and decisions to pursue computer science related majors. We found that students who used pair programming produced better programs, were more confident in their solutions, and enjoyed completing the assignments more than students who programmed alone. Moreover, pairing students were significantly more likely than non-pairing students to complete the course, and consequently to pass it. Among those who completed the course, pairers performed as well on the final exam as non-pairers, were significantly more likely to be registered as computer science related majors one year later, and to have taken subsequent programming courses. Our findings suggest that not only does pairing not compromise students' learning, but that it may enhance the quality of their programs and encourage them to pursue computer science degrees.
Charles E. McDowell, Linda L. Werner, Heather E. Bullock, Julian Fernald
ICSE4
2002 The effects of pair-programming on performance in an introductory programming course
abstract
The purpose of this study was to investigate the effects of pair-programming on student performance in an introductory programming class. Data was collected from approximately 600 students who either completed programming assignments with a partner or programmed independently. Students who programmed in pairs produced better programs, completed the course at higher rates, and performed about as well on the final exam as students who programmed independently. Our findings suggest that collaboration is an effective pedagogical tool for teaching introductory programming.
Charles E. McDowell, Linda L. Werner, Heather E. Bullock, Julian Fernald
SIGCSE4