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Richard B. Lam

dblp:73/3579 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2005
—ORCID · none

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

Databases, data management, data science and information retrieval · 1Applied, interdisciplinary, general and emerging 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.

Human-computer interaction and pervasive computing
1 paper
Learning and educational technologies · 100%
Databases, data mining, and information retrieval
1 paper
Data mining · 100%

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

TopicWeightPapersLastEvidence papers
Learning and educational technologies › learning analytics
classroom analytics
0.112005
The classroom sentinel: supporting data-driven decision-making in the classroom · WWW 2005
Data mining
pattern mining
0.012005
The classroom sentinel: supporting data-driven decision-making in the classroom · WWW 2005

Methods — techniques the papers use, named apart from their topics

data mining · 0.1
YearPublicationVenuePosition
2005 The classroom sentinel: supporting data-driven decision-making in the classroom
abstract
Whereas schools typically record mounds of data regarding student performance, attendance, and other behaviors over the course of a school year, rarely is that data consulted and used to inform day-to-day instructional practice in the classroom. As teachers come under increasing pressure to ensure success for all of their students, we are attempting to provide tools to help teachers make sense of what is happening in their classrooms and take appropriate proactive and/or remedial action. One such tool is a Web service we've dubbed the Classroom Sentinel. The Classroom Sentinel mines electronic gradebook and other student information system data sources to detect critical teaching and learning patterns and bring those patterns to the attention of the teacher in the form of timely alerts. In this paper, we introduce the notion of classroom patterns, present some examples, and describe a framework for alert generation and delivery.
Mark K. Singley, Richard B. Lam
WWW2