Factor Analysis of a Search Self-Efficacy Scale

Brennan, Kathy; Kelly, Diane; Zhang, Yinglong

doi:10.1145/2854946.2855002

Cited by 7 publications

(3 citation statements)

References 7 publications

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“…Participants' search self-efficacy was measured with the Search Self-Efficacy scale [9], which contains 14 items describing different search activities. Participants indicated their confidence in completing each activity using a 10-point scale, where 1=totally unconfident and 10=totally confident.…”

Section: Participantsmentioning

confidence: 99%

Towards a model for spoken conversational search

Trippas

Spina

Thomas³

et al. 2020

Information Processing & Management

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Conversation is the natural mode for information exchange in daily life, a spoken conversational interaction for search input and output is a logical format for information seeking. However, the conceptualisation of user-system interactions or information exchange in spoken conversational search (SCS) has not been explored. The first step in conceptualising SCS is to understand the conversational moves used in an audio-only communication channel for search. This paper explores conversational actions for the task of search. We define a qualitative methodology for creating conversational datasets, propose analysis protocols, and develop the SCSdata. Furthermore, we use the SCSdata to create the first annotation schema for SCS: the SCoSAS, enabling us to investigate interactivity in SCS. We further establish that SCS needs to incorporate interactivity and pro-activity to overcome the complexity that the information seeking process in an audio-only channel poses. In summary, this exploratory study unpacks the breadth of SCS. Our results highlight the need for integrating discourse in future SCS models and contributes the advancement in the formalisation of SCS models and the design of SCS systems.

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Section: Participantsmentioning

confidence: 99%

Towards a model for spoken conversational search

Trippas

Spina

Thomas³

et al. 2020

Information Processing & Management

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“…Mental models can change as new information is interpreted and new understandings are constructed or altered to fit [66]. Any misalignment between interpretation and reality can negatively affect people's mental models and their self-efficacy [67][68][69].…”

Section: Theoretical Underpinnings: Activitiesmentioning

confidence: 99%

“Creatures of habit”: influential factors to the adoption of computer personalization and accessibility settings

Wood

Griffith

Jordan

et al. 2023

Univ Access Inf Soc

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Purpose: Customizing the accessibility and ease-of-use settings of a computer can improve the overall user experience for people with and without disabilities. However, the adoption of such settings remains poor. This study investigates why various factors may influence people as they personalize and when they choose to integrate those changes into everyday use. Methods: To better understand how these factors may impact people’s personalization process, we conducted a series of interviews involving 15 people with and without disabilities across several months in 2020 when computer usage became required due to the COVID-19 lockdown. We used grounded theory to analyze 49 semi-structured interviews with participants. During these interviews, people reflected upon: past attempts at personalization using built-in accessibility or ease-of-use features of their Operating System (OS) or other assistive technologies (AT), current customization activities using the personalization software, Morphic, and future opportunities for personalization systems and features. Results: We identified several barriers, facilitators, and perpetuating factors that can influence why and when people choose to adopt and integrate their personalization changes. We also outline the overall personalization lifecycle, which illustrates when various factors may impact computer personalization. Conclusion: Personalization activities are complex and easily affected by an ecosystem of influential factors that surround them. When paired with the three design considerations and ten lessons learned from this qualitative study, the overall personalization lifecycle may be useful during the design and development of future personalization systems or features for people with and without disabilities.

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“…These surveys help to understand the students' contexts, and situate them as learners performing long‐term information searching. The components of the survey are adapted from established instruments, such as Intrinsic Motivation Inventory (Ryan, 1982), Self‐Regulation Questionnaire (Brown et al, 1999), Metacognitive Awareness Inventory (Schraw & Dennison, 1994; Terlecki & McMahon, 2018), Search Self‐Efficacy Scale (Brennan et al, 2016), Note Taking Strategies Inventory (UMass Amherst Student Success, 2021), and others. The two synchronous sessions, SES and SES3, are online observations with screen, audio, and search‐log recording.…”

Section: Lonitudinal Study Designmentioning

confidence: 99%

A Longitudinal Study to Understand University Students' Searching as a Learning Process

Bhattacharya

2022

Proceedings of the Association for Information Science and Tech

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Learning, or addressing a gap in one's knowledge, is an important motivator behind information‐seeking activities. The Search as Learning research community advocates that information search systems should be reconfigured to become educational platforms to foster learning and sensemaking. Modern search systems have yet to adapt to support this function. An important step to foster learning during search is to identify behavioral patterns that distinguish searchers gaining more vs. less knowledge during search. Previous efforts have primarily studied searchers in the short term, typically during a single lab session. Researchers are concerned over this ephemeral approach, as learning is not fleeting, and takes place over time. We propose an exploratory longitudinal study to analyze the long‐term searching behaviour of students enrolled in a university course, over the span of a semester. Our research aims are to identify if and how students’ searching behaviour changes over time, as they gain new knowledge on a subject; and how processes like motivation, metacognition, self‐regulation, and other individual differences moderate their “searching as learning” behaviour. Findings from this exploratory longitudinal study will help to build improved information search systems that foster human learning and sensemaking.

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Factor Analysis of a Search Self-Efficacy Scale

Cited by 7 publications

References 7 publications

Towards a model for spoken conversational search

Towards a model for spoken conversational search

“Creatures of habit”: influential factors to the adoption of computer personalization and accessibility settings

A Longitudinal Study to Understand University Students' Searching as a Learning Process

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