Demo Data from SIGIR 2026 / reviewers in the wild / expert
Ariana Mann
dblp:122/4823
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Human-computer interaction and ubiquitous computing · 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 |
Interaction techniques and input · 77% User interface design and tools · 23% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Interaction techniques and input
pen input |
0.1 | 1 | 2012 | The impact of interface affordances on human ideation, problem solving, and inferential reasoning · ACM Trans. Comput. Hum. Interact. 2012 |
User interface design and tools › interaction design
interface affordances |
0.0 | 1 | 2012 | The impact of interface affordances on human ideation, problem solving, and inferential reasoning · ACM Trans. Comput. Hum. Interact. 2012 |
Methods — techniques the papers use, named apart from their topics
linear regression · 0.1controlled study · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | The impact of interface affordances on human ideation, problem solving, and inferential reasoningabstractThis article presents two studies investigating how computer interface affordances influence basic cognition, including ideational fluency, problem solving, and inferential reasoning. In one study comparing interfaces with different input capabilities, students expressed 56% more nonlinguistic representations (diagrams, symbols, numbers) when using pen interfaces. A linear regression confirmed that nonlinguistic communication directly mediated a substantial increase (38.5%) in students' ability to produce appropriate science ideas. In contrast, students expressed 41% more linguistic content when using a keyboard-based interface, which mediated a drop in science ideation. A follow-up study pursued the question of how interfaces that prime nonlinguistic communication so effectively facilitate cognition. This study examined the relation between students' expression of nonlinguistic representations and their inference accuracy when using analogous digital and non-digital pen tools. Perhaps surprisingly, the digital pen interface stimulated construction of more diagrams, more correct Venn diagrams, and more accurate domain inferences. Students' construction of multiple diagrams to represent a problem also directly suppressed overgeneralization errors, which were the most common inference failure. These research results reveal that computer interfaces have communications affordances which elicit communication patterns that can substantially stimulate or impede basic cognition. Implications are discussed for designing new digital tools for thinking, with an emphasis on nonlinguistic and especially spatial representations that are most poorly supported by current keyboard-based interfaces. Sharon L. Oviatt, Adrienne Cohen, Andrea Miller, Kumi Hodge, Ariana Mann |
ACM Trans. Comput. Hum. Interact. | 5 |
| 2011 | Designing Interfaces that Stimulate Ideational Fluency in Science
Sharon L. Oviatt, Adrienne Cohen, Ariana Mann |
CogSci | 3 |