Information Literacy as a Predictor for Driving Data Literacy in Academic Library

Information Literacy as a Predictor for Driving Data Literacy in Academic Library
¹Juliet C. Alex-Nmecha, Cln, Phd, ²Samuel O. Egbo, Cln

¹Rivers State University Central Library

²Department of Library and Information Science, Faculty of Education, University of Port Harcourt

DOI: https://doi.org/10.51244/IJRSI.2025.12010053

Received: 05 January 2025; Accepted: 14 January 2025; Published: 15 February 2025

ABSTRACT

In virtually every aspect of human endeavour, there is the need for information and information literacy, in particular, to excel in evaluating the sources of data and the appropriate manipulations required. An individual with the necessary information to solve a problem is weighty and not easily swayed. Information is key moreover, when it complements the reason for which it was born.  Literacy is the ability to read and write, which is basic through being literate it extends to how an individual can explore other aspects to find a way to do things effectively. Hence, literacy is getting it done in the realm of information.  Information literacy as a predictor of driving Data Literacy is apt in this era of Data increase and technological advancement. Librarians need information literacy to drive data literacy which is the ability to drive meaningful information from data.  The study adopted descriptive Survey Research design and 85 total population of librarians in the five (5) Tertiary institutions in Rivers State, Nigeria were used. Three objectives and three research questions guided this study. the questionnaire tagged Questionnaire for Information Literacy as a Predictor for Driving Data Literacy:( QILPDDL) was used. This study, therefore, showcased the yardstick used in information literacy and determine the degree of readiness by librarians to embrace data literacy alongside information literacy.

Keywords: Information Literacy, Academic Library, Data Literacy, Literacy, Information

INTRODUCTION

Today, the world clamours for literacy in all sectors, namely information, statistics, digital, culture, data, and others. The more people remain literate about what is happening around them and in society at large, the better society functions.

Literacy is one’s ability to know, understand and utilize the assignments before us. Literacy is all about competence towards a specified area of study or discipline which has made one proficient in the act showcasing the ability to express thoughts and ideas required.

Among the contemporary types of literacy like digital, financial, media, scientific, art, information, technology and data literacies one may think they are dormant but they boost the day-to-day activities of the society and the world around us. In all types of literacy, each link connects and supports the other for a sustainable drive of the activities they perform in various organisations, including libraries. According to Shield (n.d), evaluating information is a key element in information, statistical, and data literacy.  The literacies augment the role each performs. As such, all three literacies are interrelated. It is difficult to promote information literacy or data literacy without promoting statistical literacy and others. While their relative importance varies with one’s perspective, these literacies are united in dealing with similar problems that face students, researchers, and information seekers. Information literacy is critically important because we are surrounded by a growing ocean of information in all formats (Thanuskodi, 2019).

The term information literacy is an aspect of literacy that connects wider dots other literacies. Information is important for the upkeep of the jobs that the librarians do. Nothing thrives without the needed information, therefore, information according to Sir Francis Bacon is power. Being literate in information is an ideal yardstick for providing growth and advancement.

Information literacy is knowing when and why you need information, where to find it, and how to evaluate, use and communicate it ethically (University Libraries).

Information literacy (IL) according to Bent and Stubbings (2011), is a set of seven skills: identifying (recognising information needs), scoping (distinguishing ways of addressing information gaps), planning (constructing strategies for locating information), evaluating (comparing and evaluate information), managing (organise, apply and communicate information), and presenting (synthesize and create information) of information.  According to the University of North Texas (UNT), Information literacy forms the basis for lifelong learning. It is common to all disciplines, to all learning environments, and all levels of education. The gap between the available information and the skill set of information users has raised the need for individuals to acquire information and technological skills to help them become effective information users the essence of why being information literate will help to drive digital literacy (Ozor & Toner, 2022). It enables learners to master content, extend their investigations, become more self-directed, and assume greater control over their learning. To Wanner (2015), an information-literate individual can:

• Determine the extent of information needed
• Access the needed information effectively and efficiently
• Evaluate information and its sources critically
• Incorporate selected information into one’s knowledge base
• Use information effectively to accomplish a specific purpose.

Information literacy as discussed so far exhibits the qualities of a driver that will propel data literacy. Information literacy according to Hisle and Webb (2017) is a set of abilities requiring individuals to recognise when information is needed and have the ability to locate it and evaluate it. and use it effectively.

Society is becoming increasingly reliant on data, ensuring that all citizens are equipped with the skills needed to be data literate (Annika.  Daniel, Jose, and Gerd 2016). Data literacy, also known as data fluency, recognises context and language in understanding data. To Fernandez (2023) data literacy can help individuals and organizations like academic libraries to improve customer (user) service, reduce costs and increase profits, manage risk more effectively, make better use of resources, create a more data-driven culture and build stronger data governance postures. These improvements come about as a result of several key benefits of data literacy:

• Improved decision-making: Data literacy helps individuals and organizations make better decisions by providing them with the ability to understand and analyze data.
• Increased productivity: Data literacy increases visualization and analytics, which in turn affects performance. This allows companies to solve problems more rapidly and efficiently, as well as potentially increasing sales and production or decreasing costs and risks.
• Increased reputation and innovation: Through data literacy, companies can build brand reputation benefiting their workers and customers, and by fostering innovation, they can be first in line for new opportunities and technologies.
• Enhanced communication: Understanding data enables employees to better communicate complex data analysis clearly and concisely, thus improving collaboration.

The fact that information literacy is an umbrella word housing the various types of literacy makes it pretty vital to be an open programme for every librarian to get involved in and adopt as a key pointer to gaining knowledge about data acquisition, manipulations and interpretation. Prado and Marzal (2013) posit that data literacy is the component of information literacy that enables individuals- to access, interpret, critically assess, manage, handle and ethically use data. He further posits that academic libraries work hard to enhance the data literacy level of librarians alongside information literacy. Finally, as much as the knowledge of information literacy – the ability to know when one needs information, how to find the information and assess it and its numerous formats gives an insight into what to benefit from it. With these components IL has like find, evaluate, organize, use, communicate and interpret information. The drive for data literacy with these components helps make it easier and understandable however, there is a dearth of literature on how IL will drive the DL, hence this work to bridge the gap and contribute to knowledge.

Problem Statement

The growing social importance of data and its utilization in every sector of society is a concern of information professionals and other organizations who aspire to get data collection, analysis, interpretation and presentation right to draw up valuable objectives and decisions to smoothly run the organization. Academic libraries are known for the acquisition, selection, cataloguing and classification of information materials that aid teaching, learning, and research in their various institutions. Having these specifications in mind the need for fluent data keeping which starts from its collections is sacrosanct as information literacy is too. Therefore, the drive to hitch-free data literacy is predicted to be achieved through information literacy hence this study further buttresses the assertion.

Objectives of the study

1. To investigate how the knowledge of information literacy will spur data literacy in academic libraries
2. To determine the yardsticks that information literacy employs to drive data literacy
3. To ascertain whether academic libraries upgrade information literacy programmes to drive data literacy

Research Questions

1. Do the knowledge of information literacy spur data literacy in academic libraries?
2. Are there yardsticks employed through information literacy to drive data literacy?
3. Do academic libraries upgrade information literacy programmes to drive data literacy?

BRIEF LITERATURE REVIEW

Information is like a vehicle sent on an errand that knows exactly where it was sent to. With information, people are informed on the right way to handle activities and draw up recommendations where necessary. Being information literate enables one to get involved in the intellectual framework for identifying, finding, understanding, evaluating and using information; it also includes determining the nature and extent of needed information, accessing information effectively and efficiently evaluating critically information and its sources incorporating selected information in the learner’s knowledge base and value system… the authors concluded as cited from Ojodokun (2007) that information literacy presupposes that an individual recognizes the need for information, and knows how to find, evaluate, use, and subsequently communicate information effectively to solve particular problems or to make decisions (Ojo, Odunlade and Adedokun, 2020). From the above explanation of what IL is driving at, data literacy (DL) is explicit, collated and clarified using IL. To Ezeani (2016) information literacy is a major task for academic libraries as a research centre stage. They are mandated to offer bibliographic instructions to their patrons even as they ensure the librarians are trained in information literacy programmes through organized workshops to enable them to carry out their services and harness information effectively. Thanuskodi (2019) in his study quoted Johnson (2012), Koltay (2016), Pothier and Condon (2019), Haendel et al. (2012) that data literacy extends to the skills required for sorting, processing, and filtering vast amounts of data, including search techniques, sorting algorithms, filtering mechanisms, and data processing methods. He went further to state that data literacy shares similarities with information literacy and serves similar objectives hence, discovered that organizations face challenges in transitioning to data-centric infrastructures due to a lack of individuals equipped with data literacy skills. Given the continuous growth of data and the limited pool of individuals proficient in handling it, the urgency and significance of fostering data literacy should not be underestimated

According to Ghodoosi, West, Li, Torrisi-Steele and Dey (2023), enormous volumes of data are generated continuously by the digital world. Data is only useful if people are data literate, have adequate knowledge or skills to find, collect, analyze, and evaluate, understand, and critically apply the data. Actualising this the need for information literacy is paramount. Data literacy enables everyone to ask the right questions, gather the right data and connect the right data points to derive meaningful and actionable business insights. It even ensures employees understand how to manage and use data in ways that are ethical and compliant Data literacy is unquestionably important as an emerging literacy, and scholars are still grappling to understand exactly what it encompasses, especially since data literacy may have different interpretations in different contexts (University of North Texas University Libraries,2024).

The concept of data literacy refers to “the ability to transform information into actionable instructional knowledge and practices by collecting, analyzing, and interpreting all types of data” (Gummer and Mandinach, 2015 as cited by Henderson and Corry, 2021). In data literacy as posited by Morrow (n.d), 3Cs are involved to effectively work on data. These are Curiosity, Creativity, and Critical thinking. The area of curiosity has to do with the ability to ask questions and challenge activities. The more questions human beings pose the more data are created and invariably the questions asked answers are provided. For creativity, it helps in the ability to analyse the data in different ways. This idea creates a better story and is fine-tuned. For all these to be put together and get meaningful explanations that will aid the manipulation of data human critical thinking is vital.

METHODOLOGY

The study adopted the descriptive survey research design. This method is relevant to this study because it engages the people (librarians) at the centre of the research objective, using both qualitative and quantitative descriptive purposes. The population of this study is eighty-seven (87) librarians from tertiary institutions in Rivers State, Nigeria. These librarians are from: the University of Port Harcourt (23 Librarians), Rivers State University (23 Librarians), Ignatius Ajuru University of Education (19 Librarians), Captain Elechi Amadi Polytechnic (14 Librarians), and Kenole Polytechnic Bori (8 Librarians).

Considering the small population size, the total enumeration method (census) was adopted to cover all 87 librarians across the academic libraries in Rivers State, Nigeria. The instrument found suitable for this study is the questionnaire tagged Questionnaire for Information Literacy as a Predictor for Driving Data Literacy:( QILPDDL) which was answered using the four-point Likert scale of Strongly Agree (SA), Agree (A), Strongly Disagree (SD) and Disagree (D). Out of the 87 copies of the questionnaires distributed 85 were retrieved and found valid for analysis. The data was analysed using a frequency count of simple percentages. Table 1 shows the representation.

Data Analysis and Discussion of Findings

The information about the number of librarians and institutions is represented in Table 1 below and the data was analyzed using frequency and percentage. For the decision rule, 2.5 was used as the hypothetical cut-off point, a value obtained by adding the exact upper limit of the scale (4) and the exact lower limit of the scale (4) and dividing by two. Therefore, research items in which the respondents score a mean of 2.5 and above are regarded as being significantly related to the study and the research questions asked proved positive.

Table 1: Population Distribution:

SN	INSTITUTIONS	POPULATION SAMPLED	RETURNED	PERCENTAGE
1	University of Port Harcourt, Choba	23	23	27.1
2	Rivers State University, Nkpolu-Oroworukwo Port Harcourt	23	22	25.9
3	Ignatius Ajuru University of Education, Rumuolumeni	19	18	21.2
4	Captain Elechi Amadi Polytechnic, Rumuola	14	14	16.5
5	Kenole Polytechnic, Bori	8	8	9.4
	TOTAL	87	85	100

Source: Field Survey, 2024

*Census sampling technique was used to sample all 87 members of the population, 85 were correctly filled and returned, indicating a 97.7% response rate.

Presentation and Discussion of the Findings

This section of the paper presented and discussed the findings according to the research questions designed for the study.

RQ 1: Do the knowledge of information literacy spur data literacy in academic libraries?

Table 2: Mean opinion on Knowledge of Information Literacy spur data literacy

	LITERACY	SA	A	SD	D	Mean	Decision
1	Literacy is the ability to read, write, and show competence towards specified areas of discipline	42	36	4	3	3.38	Agree
2	To be literate is to be proficient in the contemporary types of literacy like financial, technology, media, data etc	38	45	2	0	3.42	Agree
3	Being literate is an exposure to what happens in and around the information economy of our society	47	20	10	8	3.25	Agree
4	Literacy is being able to express thoughts and ideas required to dissect a discipline	42	36	6	1	3.4	Agree
	Weighted mean					3.36	High

	INFORMATION LITERACY	SA	A	SD	D	Mean	Decision
5	Librarians need to be information literate to drive data and other literacy types	52	33	–	–	3.61	Agree
6	Information-literate librarians can explore other literacy types	62	18	3	2	3.65	Agree
7	With the competency of being information literate librarians can locate and evaluate information where necessary	42	42	1	–	3.48	Agree
8	Information literacy is well-packaged to aid in identifying, planning, gathering, evaluating, managing and presenting information	58	20	5	2	3.58	Agree
	Weighted mean					3.58	High

	DATA LITERACY	SA	A	SD	D	Mean	Decision
9	Data literacy is a vital type of literacy for skills in evaluation, analysis and data interpretation	54	31	–	–	3.64	Agree
10	Data literacy is a prerequisite to being informed on data collection to its documentation	36	42	3	4	3.29	Agree
11	Data literacy enables librarians to evaluate information and its sources critically	33	49	2	1	3.34	Agree
12	Data literacy helps individuals and organizations like libraries make better decisions by providing them with the ability to understand and analyze data	54	30	1	–	3.62	Agree
13	Data literacy creates a more data-driven culture and builds stronger data governance postures	68	17	–	–	3.8	Agree
	Weighted mean					3.54	High

Source: Field Survey, 2024

The Table 2 above shows the opinions of respondents on whether the knowledge of information literacy spur data literacy in academic literacy. The table was broken into Literacy, Information Literacy and Data literacy. These different headings brought out the knowledge of information literacy and its drive to build data literacy. The responses above showed in agreement the crucial positive impacts of information literacy to data literacy. The weighted means of these breakouts were high with Literacy having 3.36, Information literacy 3.58 and Data literacy 3.54 respectively. The weighted mean on the whole is 3.54, which is higher than 2.5 cut-off level with  which shows the importance it brings to the drive of data literacy in academic libraries.

RQ 2: Are there yardsticks employed through information literacy to drive data literacy?

Table 3: Mean opinion on the Yardsticks that Information Literacy Employs

	INFORMATION LITERACY AND DATA LITERACY	SA	A	SD	D	Mean	Decision
1	Through information literacy programmes librarians will excel in data literacy	38	45	–	2	3.4	Agree
2	Creating a course on information literacy that will house data literacy will enable librarians to be fluent in handling data	42	36	1	6	3.34	Agree
3	One of the major concerns of academic libraries is to ameliorate information literacy to boost data literacy through workshops, information literacy programmes and talk shows	62	23	–	–	3.73	Agree
	Weighted mean					3.49	High

Source: Field Survey, 2024

Table 3 above shows that academic libraries employ some yardsticks to improve data literacy. The yardsticks listed were rated high by the librarians thus the weighted mean of 3.49 showed that they were in support of the items. And also, higher than the cut-off of 2.5 level set. This finding is in consonance with Marzal (2013) who posits that data literacy is the component of information literacy that enables individuals- to access, interpret, critically assess, manage, handle and ethically use data. He further reiterates that the academic libraries work hard to enhance the data literacy level of librarians alongside information literacy

RQ 3: Do academic libraries upgrade information literacy programmes to drive data literacy?

Table 4: Mean opinion on Academic Libraries upgrades IL to drive DL

	ACADEMIC LIBRARY AND DATA LITERACY	SA	A	SD	D	Mean	Decision
1	Data literacy drive in academic libraries is championed by information-literate librarians	61	20	2	2	3.4	Agree
2	Information literacy is an engine that propels data literacy in academic libraries	48	36	1	–	3.34	Agree
3	Academic libraries organize information literacy workshops to arm the librarians on how to tackle data literacy issues that may arise while rendering services	42	38	4	1	3.73	Agree
4	Librarians improve communication skills through data literacy	36	42	4	3	3.31	Agree
	Weighted mean					3.45	High

Source: Field Survey, 2024

Table 4 above shows responses on how academic libraries work towards upgrading IL to drive DL.

The data represented in Table 4 above shows the significance of information literacy in the drive to get it right on data literacy in academic libraries. All items mean scores of 3.40, 3.34, 3.73, and 3.31 were greater than the cut-off mean score of 2.5. On the whole the total mean score of 3.45 were also greater than the cut-off mean score of 2.5. This implies that academic libraries actually upgrade on information literacy to drive data literacy. The finding is in agreement with Ezeani (2016) which posits that information literacy is a major task for academic libraries as a centre stage of research. They have the mandate of offering bibliographic instructions to their patrons even as they ensure the librarians are trained in information literacy programmes through organized workshops to enable them to carry out their services and harness information effectively. In essence, one must be literate to work on an assignment or activity involving skills.

CONCLUSION

The study examined and gave insight into the need for the knowledge of information literacy to drive data literacy. In all, there is a need to encourage librarians to improve their DL skills, and as such will enable them to experience benefits such as better data-driven decision-making on the job, career advancement, and the joy of pursuing interesting questions. Results like these take on a personal meaning, growing personal and professional opportunities however, the dearth of literature posed challenges in gathering information for this study. The results from the research questions indicated that librarians support that IL is important and need workshops, and conferences regularly to keep equipping them for activities requiring the experience gained. The growth of DL is aligned with the exposure gained from being information literate.

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