國立虎尾科技大學 |

Comparative Data Visualization Literacy Skills of Information Science Students.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Comparative Data Visualization Literacy Skills of Information Science Students./
Author:	Rogers, Monica.
Description:	1 online resource (152 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 83-12, Section: A.
Contained By:	Dissertations Abstracts International83-12A.
Subject:	Information science. -
Online resource:	click for full text (PQDT)
ISBN:	9798819394205

Comparative Data Visualization Literacy Skills of Information Science Students.
Rogers, Monica.

Comparative Data Visualization Literacy Skills of Information Science Students. - 1 online resource (152 pages)

Source: Dissertations Abstracts International, Volume: 83-12, Section: A.

Thesis (Ph.D.)--State University of New York at Buffalo, 2022.

Includes bibliographical references

Data visualization literacy can be defined as "the ability and skill to read and interpret visually represented data in and to extract information from data visualizations" (Lee, et al., 2017, p.552). Within the information science profession, data visualization literacy is an emerging and increasingly important competency within the workforce (Wright, et al., 2012; Carlson, et al., 2015; Federer, 2018). To date, there appear to be no studies addressing the data visualization literacy skills within library and information science (LIS) students, soon to be information professionals. The purpose of this quantitative study was to compare the perceived data visualization literacy skills of LIS students with their actual skills. Competency theory (Kruger & Dunning, 1999) was used as the framework for the study design and analysis of the collected data. From a participant sample of 466 currently enrolled information science students at ALA-accredited ALISE member institutions, 347 of these completed all of the required activities: the Visualization Literacy Assessment Tool (VLAT), survey demographics questions, and self-estimated scores. Findings show that 73% of participants who completed the survey and assessment scored in the top absolute quartile, and significantly underestimated their performance. However, specific gaps in relation to data visualization types (e.g., stacked bar charts and stacked area charts) were discovered, along with decreased competency as question difficulty increased. The fact that self-estimates were lower than the actual VLAT scores is contrary to competency theory findings, and information literacy studies utilizing competency theory (Kruger & Dunning 1999; Gross, & Latham, 2007, 2009, 2012; Michalak, et al., 2017). This difference may be the result of the limitation of self-selected online participants, in that participants who anticipated they would not do well on the VLAT simply may have chosen not to participate, or they dropped participation as question difficulty increased within the VLAT. To build upon or challenge the findings of this study and to attain a broader understanding of data visualization literacy skills, further research is needed, including replication studies with new cohorts of LIS students, student populations in other disciplines, and working LIS professionals.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798819394205Subjects--Topical Terms:

561178
Information science.
Subjects--Index Terms:

Data visualization literacyIndex Terms--Genre/Form:

554714
Electronic books.

Comparative Data Visualization Literacy Skills of Information Science Students.
LDR:03694ntm a22003737 4500 001 1147220
005 20240909100728.5
006 m o d
007 cr bn ---uuuuu
008 250605s2022 xx obm 000 0 eng d
020 $a 9798819394205
035 $a (MiAaPQ)AAI29209101
035 $a AAI29209101
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Rogers, Monica. $3 1472888
245 1 0 $a Comparative Data Visualization Literacy Skills of Information Science Students.
264 0 $c 2022
300 $a 1 online resource (152 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 83-12, Section: A.
500 $a Advisor: Albertson, Dan.
502 $a Thesis (Ph.D.)--State University of New York at Buffalo, 2022.
504 $a Includes bibliographical references
520 $a Data visualization literacy can be defined as "the ability and skill to read and interpret visually represented data in and to extract information from data visualizations" (Lee, et al., 2017, p.552). Within the information science profession, data visualization literacy is an emerging and increasingly important competency within the workforce (Wright, et al., 2012; Carlson, et al., 2015; Federer, 2018). To date, there appear to be no studies addressing the data visualization literacy skills within library and information science (LIS) students, soon to be information professionals. The purpose of this quantitative study was to compare the perceived data visualization literacy skills of LIS students with their actual skills. Competency theory (Kruger & Dunning, 1999) was used as the framework for the study design and analysis of the collected data. From a participant sample of 466 currently enrolled information science students at ALA-accredited ALISE member institutions, 347 of these completed all of the required activities: the Visualization Literacy Assessment Tool (VLAT), survey demographics questions, and self-estimated scores. Findings show that 73% of participants who completed the survey and assessment scored in the top absolute quartile, and significantly underestimated their performance. However, specific gaps in relation to data visualization types (e.g., stacked bar charts and stacked area charts) were discovered, along with decreased competency as question difficulty increased. The fact that self-estimates were lower than the actual VLAT scores is contrary to competency theory findings, and information literacy studies utilizing competency theory (Kruger & Dunning 1999; Gross, & Latham, 2007, 2009, 2012; Michalak, et al., 2017). This difference may be the result of the limitation of self-selected online participants, in that participants who anticipated they would not do well on the VLAT simply may have chosen not to participate, or they dropped participation as question difficulty increased within the VLAT. To build upon or challenge the findings of this study and to attain a broader understanding of data visualization literacy skills, further research is needed, including replication studies with new cohorts of LIS students, student populations in other disciplines, and working LIS professionals.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2024
538 $a Mode of access: World Wide Web
650 4 $a Information science. $3 561178
650 4 $a Educational evaluation. $3 555501
650 4 $a Science education. $3 1151737
653 $a Data visualization literacy
653 $a Science profession
653 $a Competency theory
655 7 $a Electronic books. $2 local $3 554714
690 $a 0723
690 $a 0443
690 $a 0714
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a State University of New York at Buffalo. $b Library and Information Studies. $3 1472889
773 0 $t Dissertations Abstracts International $g 83-12A.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29209101 $z click for full text (PQDT)