Perceived competence and reading enjoyment as contributors to information skills and digital technology knowledge

Authors


Abstract

This article reports on the contributions of perceived competence in information and digital skills, perceived competence in reading, and the disposition to read for enjoyment to actual performance in an information and digital literacy knowledge and skills test among 1272 eighth grade students in 20 states who participated in the study. The data support the importance of affective correlates to information sikills and digital technology knowledge, including the disposition to read for enjoyment, which is emphasized in the new American Association for School Librarian's (AASL) Standards for the 21st Century Learner. The study is grounded in Self-Determination Theory (SDT) and is part of a larger investigation on digital and information literacy and 21st Century dispositions for learning. Implications for curriculum design are discussed.

INTRODUCTION

The digital divide is a phenomenon that can be defined in simple terms as the gap between those who use digital resources, and those who do not. Related to the digital divide is the “knowledge gap hypothesis,” (Tichenor, Donohue, & Olien 1970) which suggests that as the infusion of information into a social system increases, segments of the population with higher socioeconomic status tend to acquire this information at a faster rate than the lower status segments, so that the gap in knowledge between these segments tends to increase rather than decrease.

The growth of personal computing over the last several decades has brought concerns for the digital divide to the fore in research investigations of the phenomenon of social inequality. The digital divide has been identified at two levels (Hargittai, 2002). The first-level digital divide is defined as access — or lack of access — to computing technologies and the Internet. The second level digital divide is defined as digital literacy. The distinction between two divides implies that access to information and technology resources does not equate to sophistication of use (2002).

This distinction is addressed mostly in studies of the impact of computing on social inequality. However, these two levels can be seen to apply also to information uses more broadly (such as learners' use of traditional library media and resources — books, references, etc.), in that access to resources such as those in school libraries does not guarantee use or successful performance. Student needs and the role of the librarian and other environmental supports is key.

Self-determination theory

This study is grounded in Self-Determination Theory (SDT), a macrotheory of human motivation and development, which holds that need for competence (to be effective), autonomy (to experience choice and endorsement of one's actions), and relatedness (to feel connected to others, loved, and cared for) are important motivators of human behavior, are innate needs, and are essential to psychological growth and well-being (Deci, E. & Ryan, R., 2000; Deci & Ryan, 2008). An excellent review of studies that have used SDT in education can be found in Guay, Ratelle & Chanal (2008). The needs described by SDT are central to motivation–both its type (autonomous vs. controlled) and amount (strength). For example, a student may persist in studying for an exam (a motivated behavior) because of an inherent need for competence, and may feel autonomous in taking the responsibility to do so. Further, the needs for competence, autonomy, and relatedness can be supported or thwarted by the learning environment. To put this in the context of the school library, an educator who incorporates strategies for building confidence in one's information skills and digital technology knowledge (via encouragement, practice opportunities, corrective feedback, peer tutoring, etc.) helps to create a learning environment that supports the need for competence and enhances perceived and actual competence.

While other studies have used SDT to explore perceived and actual competence in different domains, this article focuses on the domains of both information and digital literacy. It addresses the extent to which perceived competence towards information and digital skills plays a role in actual information skills and digital technology knowledge outcomes. A relationship between perceived competence and actual skills may indicate that greater support for affective learning outcomes is needed in information and digital resource contexts, to help stem knowledge gaps and the digital divide. The study also investigates whether perceived competence in reading ability and reading for enjoyment may help predict knowledge and skills in these domains.

This article presents findings for part of a larger study that includes information and digital literacy and 21st Century dispositions for learning.

LITERATURE REVIEW

Information Literacy. Information literacy has been defined by the National Forum on Information Literacy as “the ability to know when there is a need for information, and to be able to identify, locate, evaluate, and effectively use that information for the problem or issue at hand” (National Forum on Information Literacy, 2008). That information literacy (IL) is the “ability to find and use information” was also the basic definition put forth by the American Association of School Librarians (AASL) for many years in what had become a bible of sorts for school library media specialists in this country, Information Power: Building Partnership for Learning (American Library Association, 1998, p.1). New updated standards were announced in 2007 and further refined in 2008. AASL's new Standards for the 21st Century Learner encompass not only skills that contribute to multiple literacies but also their affective and motivational counterparts (2007, 2008). This is great news as a number of researchers have been arguing the critical importance of such issues in information seeking behaviors for years (Kuhlthau, 1993; Nahl, 1993; Small and Arnone, 2000; Wang et al, 2000; Bilal, 2002; Bilal and Kirby, 2002; Bilal, 2005; Nahl, 2007; Ke and Zhang, 2008). The new standards provide additional credibility to ongoing research exploring affective correlates to information seeking behaviors including the process and products of student research.

Affect refers to one's emotions or feelings while motivation refers to the direction and intensity of behavior. It is generally accepted that motivation answers the why of behavior, that is, why we persist longer or apply more effort towards one task over another. (In speaking generally of motivation, it is understood that motivation is not a unitary construct and as described earlier can be differentiated into types such as autonomous and controlled.) Studies have shown that motivational factors can impact feelings or affect.

The new AASL standards address affective issues, in part, through the incorporation of dispositions in action. A disposition has been defined as a “tendency to exhibit frequently, consciously, and voluntarily a pattern of behavior that is directed to a broad goal” (Katz, 1993). As described earlier, motivation is responsible for the direction and intensity of an individual's effort toward achieving a goal. Thus, a disposition can have motivational power behind it in that it is goal-directed. Several examples of dispositions in action from the new AASL standards include:

  • Show an appreciation for literature by electing to read for pleasure and expressing an interest in various literary genres.

  • Demonstrate personal productivity by completing products to express learning.

  • Demonstrate persistence by continuing to pursue information to gain a broad perspective.

Digital Literacy

Research into digital literacy is a multi-disciplinary endeavor that in many ways has paralleled the information literacy research. Digital literacy (DL) as a concept has roots in the long-standing media literacy program of research and pedagogy in the field of media studies, as well as information literacy research in the field of information studies, and studies of “technological fluency” in the education field. The main distinction that Livingstone, Van Couvering & Thumim (2005) point out between digital and information literacy is that where the latter emphasizes more broadly the identification, location, evaluation and use of any wide range of media materials, digital literacy focuses solely on uses of technological media, for information-seeking and other purposes. These authors (2005) point out that among those who already have access to technological media (i.e., those who get beyond the first key barrier to digital literacy), the key considerations for audience uses may reside within the concepts of motivation/ interest, and technology skills or depth of knowledge (literacy).

While in the library science field, the AASL's new Standards for the 21st Century Learner focus not only skills that contribute to multiple literacies, but also their affective and motivational counterparts (2007, 2008), the most recent National Educational Technology Standards (NETS-S) and Performance Indicators for Students published by ISTE in 2007 do not specify motivation or affect. However media scholars such as Livingstone et al (2005) are recognizing that motivation and skills play a significant role in individuals' technology uses. This study explores the relationships extant among U.S. 8th-graders' information and digital technology confidence and motivation, and information and digital technology competencies and skills. The purpose of this article is to report on the contributions of perceived competence in information skills, perceived competence in digital technology activities, perceived competence in reading, and the disposition to read for enjoyment, to performance in both a) an IL knowledge test (focusing on a range of information literacy skills as specified by the Association of School Librarians' national information literacy standards outlined in Information Power: Building Partnerships for Learning, 1998), and b) a DL knowledge test (focusing solely on technology skills as specified by the International Society for Technology in Education's [ISTE] NETS standards [2005]).

Perceived and actual competence in information science studies

Assessment of competence plays a dominant role in education today and library media specialists must promote IL competence across the curriculum. That school libraries and library media specialists play a critical role in overall student achievement has already been shown in a number of studies (e.g., Todd, Kuhlthau, and Oelma, 2004; Lance et al, 2000; Small et al, 2008). One key consideration in information-seeking is perceived competence, or a feeling of confidence in one's ability to successfully accomplish an information task. Nahl (1993) demonstrated that students who were more confident in their search capabilities were more successful and more satisfied in a search task; in a separate study, she found that college seniors who indicated low confidence in their potential to do well in a course subsequently dropped the course in a matter of weeks (Nahl, 1996). In a study of young adults, Cheong (2008) discovered that perceived skill and a belief in their own problem-solving ability (in using the internet) were the best predictors of actual creative use of the internet (i.e., for website building). Research also indicates that children are able to differentiate their competence across domains (Chapman and Tunmer, 1995; Eccles et al, 1993) even as young as the third grade (Hanich and Jordan, 2004).

In a set of parallel national standards addressing technology skills more specifically, ISTE's 2007 NETS standards for students' technology fluency do not indicate any focus on affective and motivational student contributors to technology performance. However, the 2008 NETS standards for educators do. Some examples from the educators' standards reflecting an affective dimension include:

  • Teachers promote, support, and model creative and innovative thinking and inventiveness.

  • Teachers promote student reflection using collaborative tools to reveal and clarify students' conceptual understanding and thinking, planning, and creative processes

  • Teachers develop technology-enriched learning environments that enable all students to pursue their individual curiosities and become active participants in setting their own educational goals, managing their own learning, and assessing their own progress.

While the 2007 NETS student performance indicators do not indicate student affect as a consideration in developing technology skills (and appear to be more behaviorally-oriented in bent), the 2008 NETS educator guidelines promote attention to student affect and dispositions. Our exploration into the contribution of student perceived competence (affective confidence) in information and digital activities may highlight the importance of translating the affective dimensions found in the educator NETS, into future NETS standards for students, themselves.

Perceived competence in reading ability

Perceived competence in reading may also contribute to information and digital literacy actual competence, as measured in a knowledge test of each. That this basic literacy is embedded in information literacy is a logical if not obvious assumption. Perceived competence in reading has been shown to be a stable predictor of actual reading achievement (Hanich and Jordan, 2004) and predictive of academic achievement overall, and reading is necessary for use of information resources. No studies were located that explored both perceived competence in information or digital activities, nor have we located prior studies addressing perceived competence in reading as predictors of actual information skills or digital technology knowledge.

Reading for enjoyment

Reading is not only a foundational skill for all learning and a key indicator of success in school and in life, but it is also required for personal growth and enjoyment (2007). Reading for enjoyment, which is sometimes referred to as reading for pleasure, independent reading (Cullinan, 2000), and voluntary or self-selected recreational reading (Krashen, 2004), has also been positively associated with actual or perceived reading ability (Clark & Rumboldt, 2006; The Reading Agency, 2003). Reading for pleasure is intrinsically motivated behavior. That is, the satisfaction is intrinsic to the activity itself. Clark and Rumboldt (2006) define it as “reading that we do of our own free will anticipating the satisfaction that we will get from the act of reading.” We empirically explore the contribution that a disposition toward reading for enjoyment would make to both information skills and digital technology knowledge, as stipulated by the AASL standards and definitions.

The Research Model

Six hypotheses were explored in a multiple correlation study. We tested whether perceived competence in information skills, perceived competence in reading, and the disposition to read for enjoyment could help explain some of the variation in scores in a test of IL knowledge and skills. We then added two more predictors, which are often used in predicting achievement (parent education and grades) to test the robustness of the motivational model. We also conducted a parallel analysis involving students' perceived competence in digital technology activities, and a test of digital technology knowledge, along with the same other constructs.

Scholarly exploration of perceived competence in information literacy (IL) skills have been found for teachers and young adults (e.g., Kurbanoglu, Akkoyunlu, and Umay, 2006), but research studies addressing younger students are much needed. As for perceived competence (i.e., confidence in one's ability to engage) in digital technology activities, our research model appears to be the first developed that is testing aspects of Deci and Ryan's self-determination theory, in the technology and information context.

We chose eighth grade as our sample population because information and technology competency assessments typically occur at the 8th grade level in great part due to mandated requirements of the NCLB Act (2001). Assessment methods, however, are not mandated and can be determined by the school. They can include knowledge-based tests, rubrics, checklists, portfolios or other means (Dow, 2007). Some schools deliver a knowledge-based test at the beginning of 8th grade as a pre-assessment to identify information and technology skills that need to be addressed, and then again at the end of the year to determine if improvement has been made. Tests can provoke anxiety among students due, in part, to the fear of personal evaluation or not living up to their own or teacher expectations. This may especially be true in the area of information skills targeted towards the use of technology – an important aspect of overall information literacy elaborated in the new standards. In this regard, a 2008 report of the National Education Association concludes that although all educators and students in public schools have some access to computers and the Internet, “we have few assurances that they are able to use technology effectively for teaching and learning” (NEA, 2008).

Findings for students at the 8th-grade level on the contribution of perceived competence in information and digital technology skills to actual skills knowledge, can inform research, as well as practice to better prepare students in this domain of learning. If perceived competence in these skills is found to be predictive, an instrument focused on this affective construct can be developed and used as a proxy diagnostic in the school setting by the library media specialist and classroom teachers, who can use the results to identify and address gaps in student confidence through the design of appropriate instructional interventions. The passage from middle school to high school represents a critical childhood transition. Further, understanding the relationship between students' perceptions of their own information literacy abilities, and their actual skills, could confirm the relationship between affect and actual skills in the library context. These results can aid library media specialists and classroom teachers in targeting and developing interventions toward skill areas in which students lack confidence. Thus, hypothesis #1 and 2 are stated below.

  • The higher a student's perceived competence in information skills, the higher will be performance in a knowledge test of information literacy.

  • The higher a student's perceived competence in digital technology activities, the higher will be performance in a knowledge test of digital literacy.

The National Assessment of Educational Progress report (2007) indicated that only about 29% of eighth graders were proficient in reading. Students with only basic level reading skills no more than partially master the knowledge and skills required for achievement at grade level. This finding provides justification that perceived competence in reading would also explain some of the variation in scores on an achievement test in the IL and DL domains of knowledge. Thus, hypothesis #3 and 4 are:

  • The higher a student's perceived competence in reading, the higher will be performance in a knowledge test of information literacy.

  • The higher a student's perceived competence in reading, the higher will be performance in a knowledge test of digital literacy.

Reading for enjoyment/pleasure or self-selected recreational reading (Krashen, 2004) has been positively associated with actual or perceived reading ability (Clark & Rumboldt, 2006; The Reading Agency, 2003) but we found no studies that explored this construct with respect to IL or DL competence. For this reason, we proposed hypothesis #5 and 6.

  • The greater a student's disposition to read for enjoyment, the higher will be performance in a knowledge test of information literacy.

  • The greater a student's disposition to read for enjoyment, the higher will be performance in a knowledge test of digital literacy.

METHODS

Sampling and Procedures. The project began with an initial pilot study conducted as an online survey with a convenience sample of 9 schools with 279 students in the fall of 2007. The results of the pilot were used to refine instruments for the main study.

The main study data collection was conducted in the Spring of 2008 with a large convenience sample of U.S. 8th grade students and their teacher/librarians (note: this job title is used interchangeably with the terms school librarian and library media specialists). Main study schools were recruited during January and February 2008 from open invitations posted to the mailing list of the American Association of School Librarians Forum (AASL Forum) and to the listserv of Tools for Real-Time Assessment of Information Literacy Skills (TRAILS-9). Interested individuals completed an initial online interest questionnaire which provided information about the study and collected demographics and contact information. A small gift of $200 to be used in the school library media center was provided as an incentive for participation in the full study.

Library media specialist participation in the study both as administrators and participants was an important aspect of the study. Evidence-based practice by teacher-librarians has been encouraged in the past several years in the literature (e.g., Loertscher & Todd, 2003). It is accomplished through action-based research in which the library media specialist collects data in order to improve instruction or some aspect of the library media program. For this reason, as further incentive we also offered to share school-level datasets and a results profile report to each participant school presenting school-level anonymized aggregate findings from the three student surveys.

Participants

Eighty schools initially agreed to participate in response to the listserv solicitations, but some determined the schedule of participation would be too demanding (given 3 survey sittings). Ultimately, 47 schools fully participated in all three sessions of the survey data collection. The 47 schools included 46 teacher-librarians. There was some attrition in students at each location across the three survey sittings, which is reflected in some of the varying Ns for the descriptive statistics below. The N for Survey Sitting 1 was 1264. The N for Survey 2 was 1180. The N for Survey 3 was 1028. Furthermore, not all students answered each question. For example, not all students knew their parents' education levels and thus that question reflected a lower response rate (n = 933). An average of 27 adolescents (average age of 13) participated from each school. Twenty U.S. states were represented in the sample. The geographical distribution, socio-economic status, and setting of the schools sampled are indicated in Table 1. The data source for Table 1 is the pre-screening participant recruitment survey for the 47 librarian participants. Each library media specialist and student guardian was requested to complete a consent form for participation, providing permission and assuring participant anonymity and privacy.

Table 1. 
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Protection of Minors

Syracuse University Institutional Review Board (IRB) approved this project and all of its pilot and full study components, instruments and procedures. Participation was voluntary and signed parental/guardian permission forms were acquired for student participation for all 1272 students with copies of permission forms residing both at Syracuse University and with the participating schools. Additionally, the administrator protocol required library media specialists to orally inform students that their participation was voluntary and that they could withdraw from the study at any time. As another measure of protection, each online survey session began with a written reminder that participation was voluntary and withdrawal at any point in the study was permitted. Skipping questions was permitted. They were also made aware that their responses to the survey would remain anonymous. No limitations were placed on time allocation and students' time to complete each of the surveys ranged from 25 to 35 minutes.

Training

The teacher/librarians were trained to implement the surveys through their study of the online instructions provided on the project training website. Participants did not know the specific content of the questionnaires prior to administration. School librarians were instructed to choose students randomly, or to implement the survey within a class that they perceived to be representative of the school's student body as a whole. Each participant was emailed an Excel spreadsheet for his/her school, providing unique participant ID numbers. A survey administration script, the online survey links, and two support phone numbers were also provided. Participating schools carried out a hardware and software compatibility test to ensure browser compatibility when linking to surveys. School librarians had flexibility in determining the most convenient times for them to access and administer the sessions, however all three surveys were completed within an 8-week timeframe at each location, as requested. The development of the instruments used in both the pilot and main studies are discussed in a separate article currently in production. The ethnic backgrounds and gender of the student participant sample are given in Tables 2 and 3 below, derived from the full study student survey as data source. The convenience sample appears to over-represent white students and under-represent black and Hispanic/Latino students.

Table 2. 
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Table 3. 
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Measures

A number of measures were used to test the stated hypotheses. They included the following. Information Literacy Knowledge Test. This measure was provided to the authors by researchers from Kent State University who developed and validated the 30-item TRAILS test, Tool for Real-time Assessment of Information Literacy Skills (Schloman and Gedeon, 2007). The TRAILS test was developed for 9th graders. Since our subjects were 8th graders, the researchers worked with us to identify items from the original test that skewed lower on the item difficulty index. It was used in the pilot with 20 of the 30 items from the general assessments. The decision to reduce the number of items in the pilot was made to lessen the cognitive load on students who were also completing other questionnaires. Based on the post-pilot item analysis, we replaced items that skewed as too difficult or too easy, added 5 more items from the TRAILS item pool to increase reliability, and used the revised version in the main study. The Cronbach's alpha reliability coefficient in the final 25-item version was acceptable at.81.

Digital Literacy Knowledge Test

This measure was provided to the authors by researchers at LearningPoint Associates, a private research consulting organization that conducts national research for a range of vertical markets. Their technology literacy test was developed based on the ISTE NETS standards as of 2005, targeted toward students at the 8th-grade level. On the whole, the knowledge test asked students to identify the meaning, functionality, and appropriate use case scenarios of various basic desktop technology tools and activities, for instance, engaging in online search, using various standard software tools such as MS Excel and Word, the purpose of a database, etc. Their overall assessment of the student NETS test met generally accepted levels of reliability and content and construct validity in empirical validation conducted with over 2000 pupils (LearningPoint, 2005). The 84 resulting items that were retained fit the Rasch model expectations, and the overall reliability of.88 was within accepted norms. In addition, an external panel of educational technology experts reviewed the content validity of each item on several criteria by using procedures outlined earlier in the paper. Once the items were generated, their panel of experts convened to validate the items. This panel rated each item on the criteria listed following a three-stage process involving an item-by-item analysis, evaluation of challenge, and evaluation of balance and range. The researchers state, “we are confident that it resulted in the development of items that are much more closely aligned with the NETS” (LearningPoint, 2005).

Our advisor at LearningPoint recommended that given our study constraints and concerns about survey fatigue, we narrow our use of the questions to those within the Basic and Proficient levels of difficulty (comprising 46 questions). The contact ran analysis of just these items, resulting in Rasch reliability of.79, also deemed acceptable. We ultimately chose to implement a selection of 40 items from this pool of 46 items provided. We also added 5 of our own self-drafted questions, to expand the range of constructs examined, to reflect advances in digital technology since the original test was administered, such as questions on students' uses of social network sites, blogging, and specifically information-seeking type uses of technology. Two questions from the original pool of validated LearningPoint item set were skewed in our dataset and lacked fit, and thus were dropped during item analysis, leaving us a total of 43 items. We combined these items into a single test score for each student, based on correct and incorrect responses. This combined test score served as our digital knowledge construct with a Cronbach's alpha reliability coefficient of.86.

Perceived Competence in Information Skills

This instrument was refined from the pilot study and included 17 items related to specific information skills. The instrument had high internal consistency (Cronbach's α=.93). Students responded to statements on a 5-point Likert scale.

Examples of items included

I am CONFIDENT in my ability to do well in the activities listed below:

  • Formulating smaller (more specific) questions that help me narrow down my big (broad) research topic.

  • Locating information on my research topic in sources like books, databases, encyclopedias, and websites.

  • Recognizing if information I find is biased or slanted toward a particular point of view.

To establish construct validity, the PCIS was correlated with a validated instrument from the family of SDT questionnaires, the 4-item Perceived Competence in Learning scale applied to the domain of research ability (r =.74, p <.001). Establishing a significant relationship between the PCIS measure and actual performance on the IL knowledge test could also be seen as a form of concurrent validity as it was administered in the same session as the PCIS.

Perceived Competence in Technology Activities

This instrument was refined from the pilot study and included 11 items related to specific digital skills. The instrument had high internal consistency (Cronbach's α=.92). Students responded to statements on a 5-point Likert scale. Examples of items included:

  • I am CONFIDENT in my ability to be productive with technology.

  • I am CONFIDENT in my ability to express ideas with technology.

  • I am CONFIDENT in my ability to have fun with my friends with technology.

To establish construct validity, the PCTS was correlated with a validated instrument from the family of SDT questionnaires, the 4-item Perceived Competence in Learning scale applied to the domain of general technology ability (r =.71, p <.001. Establishing a significant relationship between the PCTS measure and actual performance on the DL knowledge test could be seen as a form of concurrent validity.

Reading Enjoyment

This 3-item scale was operationalized with the following items, scored on a 5-point Likert scale of 1=not at all true, 2=not usually true, 3=sometimes true, 4=usually true, 5=very true: “I read for pleasure whenever I can,” “I enjoy reading in at least one genre (e.g., fiction, non-fiction, poetry, realistic fiction, etc.),” and “I like to read in a variety of formats including books, magazines, and the Web.”

Table 4 shows the composite reliabilities of each of the construct measures.

Table 4. 
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Perceived Competence in Reading

Perceived competence in reading is the traditional literacy counterpart to perceived competence in information skills. While this variable was less of an emphasis in our research than information skills, we include it in our hypotheses because it reflects another affective variable indicating one's level of confidence. This item is operationalized in our research as “Please rate yourself in terms of your reading ability” (1=poor, 2=fair, 3=good and 4=excellent).

Parent Education

Parent education was measured as an additive combined mean of two items asking, “Please choose one of your parents or legal guardians. What is the highest level of education for this parent or legal guardian?” and “Now, if you have another parent or legal guardian, what is the highest level of education for your OTHER parent or legal guardian?” Response categories included 1=did not complete high school, 2=completed high school, 3=completed high school, attended some college, 4=completed college (at least 4 years), 5=completed college, attended some graduate school, 6=completed graduate school.

Self-reported Grades

Self-reported grades was operationalized as a single item asking “What grades do you usually get on your report card?” with response categories 1= all As (or 4s); 2 = mostly As and some Bs (or 4s); 3 = mostly Bs and some Cs (or 3s); 4 = mostly Cs and some Ds (or 2s); 5 = mostly Ds and Fs (or 1s).

5

Table 5. 
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Data Analysis

We have used ordinary least squares (OLS) regression as the method for analyzing the survey data of 8th-graders. Our outcome variable of information literacy knowledge is interval level, thus this method is appropriate. We checked the correlations among the independent variables, and none of them were prohibitively high, so they may be included in the analyses simultaneously. We performed several other diagnostics to make sure our data meet the requirements of OLS regression analysis. The two tables below reflect Pearson correlation coefficients for the variables used in the information literacy models, and the digital literacy models. It appears that the relationship between the two reading variables (perceived competence and enjoyment of reading) and perceived competence in information skills may be higher than the correlation between the reading variables and perceived competence in technology activities (column 4 in both tables).

Actual information skills and digital digital technology knowledge were found to be correlated, r=.72, p<.001. Perceived competence in information skills and technology activities were also found to be correlated, r=.58, p<.001.

6

Table 6. 
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RESULTS

In order to test the study's hypotheses, we have conducted OLS regression, testing three models of 3 sets of independent variables' contribution to information skills knowledge. We tested parallel models for digital technology knowledge.

Information skills models. In the first model, we measure just the motivational variables' contribution to actual information skills, without any demographic variables. In the second model, we measure just the contribution of education demographic variables of parent education and self-reported grades, on their own, to students' performance on an information skills knowledge test — which we have hypothesized will explain some of the variance in performance on any kind of knowledge test because they are predictors of overall school achievement.

In the final model, we measure the contribution that the motivational variables for information skills make to information skills knowledge, over and above the demographic variables. If motivational variables for information skills contribute significantly over and above the educational demographic variables, we suggest that this result will lend support to our theoretical proposition regarding a relationship between perceived competence and reading and information literacy knowledge and skills. Results are presented in Table 7.

Table 7. 
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Regression results for Model 1 indicate the contribution of the motivational variables of perceived competence in information skills, enjoyment of reading, and perceived competence in reading to information skills knowledge on their own, without demographic variables. For Model 1, the R2 results are statistically significant, F(3, 1190) = 141.53, p<.001, accounting for 26% of the variation in scores for information literacy knowledge and skills.

Results for Model 2 indicate the contribution of the demographic variables of parent education and self-reported grades on their own, to information literacy knowledge. For Model 2, the R2 results are also statistically significant, F(2, 906) = 96.80, p<.001.

Results for Model 3 indicate the contribution of the motivational variables to information skills knowledge — over and above the demographic variables. For Model 3, the R2 change is.13 over and above Model 2, and results are statistically significant, F(5, 903) = 78.18, p<.001. In this model, we see that each motivational variable still contributes significantly over and above the demographic variables indicating the robustness of the motivation model. This result may indicate that the demographic variables of parent education and school performance may play a role in the mechanism by which the motivational variables of perceived competence in information skills and reading, and reading enjoyment, operate in their relation to information skills knowledge.

Overall, results support the three information literacy hypotheses posed by this study:

  • The greater a student's perceived competence in information skills, the better will be the actual performance in a knowledge test of information literacy.

  • The higher a student's perceived competence in reading, the higher will be performance in a knowledge test of information literacy.

  • The greater a student's disposition to read for enjoyment, the better will be the performance in a knowledge test of information literacy.

Regression results indicate that the three independent variables addressed in the above hypotheses all contribute significantly to information skills knowledge, over and above educational demographic variables of self-reported grades and parent education.

Digital technology knowledge models

In the first model, we measure just the motivational variables' contribution to actual digital technology knowledge, without any demographic variables. In the second model, we measure just the education demographic variables of parent education and self-reported grades' contribution, on their own, to students' performance on a digital technology knowledge test — which, as hypothesized in the information skills model, will explain some of the variance in performance on any kind of knowledge test because they are indicators of overall school achievement.

In the final model, we measure the contribution that the motivational variables of perceived competence in technology activities and reading for enjoyment make to digital skills knowledge, over and above the demographic variables. Results are presented in Table 8.

Table 8. Average Precision Summary of Each Expansion Strategy
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Regression results for Model 1 indicate the contribution that perceived competence in digital technology activities, reading ability, and enjoyment of reading make to digital technology knowledge on their own, without demographic variables. For Model 1, the R2 results are statistically significant, F(3, 1055) = 132.98, p<.001, accounting for 27% of the variation in digital technology knowledge.

Results for Model 2 indicate the contribution of the demographic variables of parent education and self-reported grades on their own, to digital technology knowledge. For Model 2, the R2 results are statistically significant, F(2, 860) = 87.97, p<.001.

Results for Model 3 indicate the additional contribution of the motivational variables to digital technology knowledge — over and above the demographic variables. For Model 3, the R2 change is.17 over and above Model 2, and results are statistically significant, F(5, 857) = 88.85, p<.001.

Overall, results support the three digital literacy hypotheses posed by this study:

  • The greater a student's perceived competence in digital technology activities, the better will be the actual performance in a knowledge test of digital literacy.

  • The higher a student's perceived competence in reading, the higher will be performance in a knowledge test of digital literacy.

  • The greater a student's disposition to read for enjoyment, the better will be the performance in a knowledge test of digital literacy.

Regression results indicate that the three independent variables addressed in the hypotheses all contribute significantly to digital skills knowledge, over and above educational demographic variables of self-reported grades and parent education.

The results for the digital technology knowledge model mirror those for the information skills model. It is interesting that perceived reading ability also played as significant a role in digital literacy as it did in information literacy. This result warrants further exploration in future studies of digital literacy.

DISCUSSION

According to self-determination theory, enhancement of perceived competence in any domain can lead to enhancement of learning outcomes and effectiveness in the same domain; in the theory, one's perceptions of competence are causal contributors to actual effectual performance. Our findings lend support to this theory, in both the information skills and digital technology domains.

Our results support the hypotheses that in both the information skills and digital technology domains, perceived competence in information skills / digital activities, perceived competence in reading, and reading enjoyment contribute to actual information skills and digital technology knowledge in 8th-graders. The motivational model addressed in this study's exploration into information literacy variables accounts for about 26% of the variation in information skills achievement as measured by the knowledge test in our sample of 8th-graders, with the amount of variance accounted for by these variables remaining at 13% when examined over and above academic demographic variables of self-reported grades and parent education. In the digital technology domain, the motivational model on its own contributes 27% of the variation in knowledge and 17% when examined over and above the contribution of self-reported grades and parent education. It appears that the demographic variables of student grades and parent education each contribute about equally, to both actual information skills and digital technology knowledge.

Further, our findings lend support to AASL's inclusion of support for affective qualities (i.e., dispositions for learning) in their new Standards for the 21st Century Learner. On the technology side, the findings also support the future inclusion of affect as a dimension of ISTE's influential NETS standards for students' technology learning moving forward.

Our findings are also important because they highlight the extent to which perceived reading ability and reading enjoyment contribute as underlying factors of information skills knowledge. The AASL standards suggest that reading is a foundational skill for all learning and a key indicator of success in school and in life, and that reading ability is also required for personal growth and enjoyment (2007). The relationships present between reading and information skills may signal that the broad construct of “information literacy” also plays a role in the outcomes of learning, personal growth and enjoyment (in that reading is one facet of constructive and dynamic application of information skills). The findings also lend empirical support to the important role that reading plays in information literacy — which has implications for information skills pedagogy of school library / media specialists. These hypotheses require further exploration.

Similarly, the results for reading and digital literacy are notable, and future research into digital literacy should address perceived and actual reading skills as a key underlying contributor to digital technology knowledge in young people. While virtual technology environments reflect an ever-growing range of multimedia beyond text, it appears that perceived reading ability plays a role in achieving the abilities reflective of the range of ISTE's NETS standards. Socio-economic status also appears to contribute to both digital and information skills of 8th-graders, to the extent that student-reported parent education level is an indicator of socio-economic status.

Implications for Curriculum Design

The results of this study highlight the need for interventions that integrate both reading (basic literacy) and information / digital literacy objectives. The study also highlights the role the teacher/ librarian may play in supporting positive student affect toward information and digital literacy. Teacher/librarians can play a role in observing certain affects and dispositions in students (higher or lower), in anticipation that these qualities will be partially predictive of corresponding information skills performance. In fact, our research may support use of the PCIS and PCTS scales to identify gaps in knowledge areas at the beginning of the year instead of using an actual knowledge pre-test, before the students have been introduced to an information and digital literacy curriculum.

Studies based on SDT have shown that student performance worsens the more pressured they feel (e.g., Grolnick & Ryan, 1987). One researcher and family therapist makes an important connection between the escalating pressure on children and adolescents due to high-stakes standardized testing and an increase in her child and adolescent patients presenting anxiety symptoms including test anxiety (Schroeder, 2006). A perceived competence test that has no right or wrong answers and for which students are informed will help their teacher-librarian and classroom teachers plan instruction seems more humane in this era of test bombardment and more conducive to establishing a supportive, less stressful learning environment. A survey of student self-perceptions at the start of the year may help the educator identify target areas for improvement, while reducing the risk in testing anxiety and a possible reduction in their perceived competence as a result of being tested on skills they have not yet been introduced to adequately in the curriculum. Educators could identify students who have low confidence in their skills without the embarrassment of scoring poorly on yet another “test” — especially one presented as a pre-test, which may be unnecessary with the availability of a shorter, affective proxy. This may allow teacher/ librarians to develop and implement customized interventions more creatively, and apply them on an individual basis at the student level, to effect improvements in information and digital literacies in the context of the curriculum.

Acknowledgements

*Special thanks to Edward E. Deci at the University of Rochester for providing guidance in the development of the PCIS measure and providing support throughout the study and to Jeff Stanton at Syracuse University for his methodological guidance. We would also like to thank Kent State researchers Barbara Schloman and Julie Gedeon for consultation on the information skills knowledge test, LearningPoint for consultation on the digital technology knowledge test, and the 46 school library media specialists and their students for participating in the study. Finally, thank you to the Institute of Museum and Library Services for providing funding for this study through a National Leadership Grant to the Center for Digital Literacy, Syracuse University.

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