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Development and preliminary testing of a self-rating instrument to measure self-directed learning ability of nursing students
International Journal of Nursing Studies 47 (2010) 1152–1158
Contents lists available at ScienceDirect
International Journal of Nursing Studies journal homepage: www.elsevier.com/ijns
Development and preliminary testing of a self-rating instrument to measure self-directed learning ability of nursing students Su-Fen Cheng a, Chien-Lin Kuo b, Kuan-Chia Lin a, Jane Lee-Hsieh a,* a b
School of Nursing, National Taipei College of Nursing, 365, Ming-Te Rd, Peitou District, Taipei 11219, Taiwan, ROC Department of Nursing, Fooyin University, Kaohsiung, Taiwan, ROC
A R T I C L E I N F O
A B S T R A C T
Article history: Received 21 August 2009 Received in revised form 12 January 2010 Accepted 7 February 2010
Background: With the growing trend of preparing students for lifelong learning, the theory of self-directed learning (SDL) has been increasingly applied in the context of higher education. In order to foster lifelong learning, abilities among nursing students, faculties need to have an appropriate instrument to measure the SDL abilities of nursing students. Objectives: The objectives of this study were to develop an instrument to measure the SDL abilities of nursing students and to test the validity and reliability of this instrument. Methods: This study was conducted in 4 phases. In Phase 1, based on a review of the literature, the researchers developed an instrument to measure SDL. In Phase 2, two rounds of the Delphi study were conducted, to determine the content validity of the instrument. In Phase 3, a convenience sample of 1072 nursing students from two representative schools across three different types of nursing programs were recruited to test the construct validity of the Self-Directed Learning Instrument (SDLI). Finally, in Phase 4, the internal consistency and reliability of the instrument were tested. Results: The resulting SDLI consists of 20 items across the following four domains: learning motivation, planning and implementing, self-monitoring, and interpersonal, communication. The final model in confirmatory factor analysis revealed that this 20-item SDLI indicated a good fit of the model. The value of Cronbach’s a for the total scale was .916 and for the four domains were .801, .861, .785, and .765, respectively. Conclusions: The SDLI is a valid and reliable instrument for identifying student SDL abilities. It is available to students in nursing and similar medical programs to evaluate their own SDL. This scale may also enable nursing faculty to assess students’ SDL status, design better lesson plans and curricula, and, implement appropriate teaching strategies for nursing students in order to foster the growth of lifelong learning abilities. ß 2010 Elsevier Ltd. All rights reserved.
Keywords: Confirmatory factor analysis Delphi study Instrument development Nursing students Self-directed learning
What is already known about the topic? A key factor affecting lifelong learning abilities is whether students have the ability to engage in selfdirected learning (SDL). There currently exist five instruments measuring SDL. However, evaluations of their psychometric properties
* Corresponding author. Tel.: +886 2 28227101x3199; fax: +886 2 28213233. E-mail address: [email protected] (J. Lee-Hsieh). 0020-7489/$ – see front matter ß 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.ijnurstu.2010.02.002
have produced mixed findings. This is probably because most of these instruments were developed using exploratory analysis. Thus far, these instruments have only been analyzed for their content and factor domains, and have not been tested for their fit with the theory. What this paper adds A Self-Directed Learning Instrument (SDLI) specifically developed and tested for nursing education, across different programs and grades.
S.-F. Cheng et al. / International Journal of Nursing Studies 47 (2010) 1152–1158
The SDLI is a reliable and valid instrument that measures four domains of SDL: learning motivation, planning and implementing, self-monitoring, and interpersonal communication. This study provides new empirical evidence and verifies the structure of the core concept of SDL. It matches empirical evidence to the theory.
1. Introduction There is a growing trend of preparing students for lifelong learning. In the field of nursing, students enter the field with extensive professional training, but must also be able to constantly update their knowledge through selfdirected learning (SDL). Thus, teaching SDL skills to nursing students helps to prepare them for success in their future careers, and enables them to engage in lifelong learning. To facilitate the development of SDL skills in nursing students, a valid and reliable tool should be made available to nursing schools to enable them to measure the SDL abilities of nursing students. Thus, the purposes of this study were (1) to develop an instrument to measure the SDL ability of nursing students and (2) to test the validity and reliability of this instrument. 1.1. Concepts of SDL According to Knowles (1975), self-directed learning is ‘‘a process in which individuals take the initiative, with or without the help of others, in diagnosing their learning needs, formulating learning goals, identifying human and material resources for learning, choosing and implement-
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ing appropriate learning strategies, and evaluating learning outcomes’’ (p. 18). Brookfield (1986) provided a similar definition of SDL. Greg (1993) argued that self-directed learners should have the ability to collaborate with peers, and see peers as learning resources. Cameron (1997) stated that a comprehensive model for SDL should involve selfmanagement, self-monitoring, and motivation. The American Association of Colleges of Nursing (2008) emphasizes the importance of communication skills in developing Baccalaureate programs and suggests that nursing faculty should design learning activities that focus on practicing communication. Based on the above discussion, the process of SDL covers the following domains: learning needs or learning motivation, learning resources, learning goals, learning plans and activities, learning evaluation, and communication skills. 1.2. Overview of existing SDL instruments The researchers used the OVID databases, bibliographies, and article references to search for existing SDL instruments. Only five instruments that directly measured SDL were found. These included Guglielmino’s (1977) SDL readiness scale, Deng’s (1995) Chinese version of Guglielmino’s instrument, Ho’s (1998) SDL ability scale, Fisher, King, and Tague’s (2001) SDL readiness scale, and Williamson’s (2007) self-rating scale of SDL. Descriptions and psychometric indices are presented in Table 1. The components of these SDL tools include: effective learning, learning motivation, active learning, independent learning, creative learning, self-management, desire for learning, self-control, evaluation, and interpersonal skills. The number of items ranged from 14 to 65.
Table 1 Reliability and validity of existing SDL instruments. Instrument
Description
Psychometric indices
Guglielmino (1977) Self-directed learning readiness scale
Defined 8 components of SDL (openness to learning opportunities, self-concept as an effective learner, initiative and independence in learning, informed acceptance of responsibility for one’s own learning, love of learning, creativity, positive orientation to the future, ability to use basic study skills, and problem-solving skills); Total items: 58 items Adapted from Guglielmino’s instrument and categorized 6 components (effective learning, love of learning, learning motivation, active learning, independent learning, and creative learning); Total items: 58 items 3 domains (planning: 6 items; self-assessment: 5 items; search for human resources: 3 items); Total items: 14
Content validity: Delphi study Construct validity: used Principle component factor analysis (PCFA), explained variance: 48%
Deng (1995) Chinese version of Guglielmino’s self-directed learning readiness scale Ho (1998) Self-directed ability scale (in Chinese)
Fisher et al. (2001) Self-directed learning readiness scale
3 components (self-management, desire for learning, and self-control); Total items: 40
Williamson (2007) Self-rating scale of self-directed learning
5 components (awareness, learning strategies, learning activities, evaluation, and interpersonal skills); Total item: 65
Translate validity Construct validity: used PCFA varimax rotation, explained variance: 89.75% Cronbach’s a .64–.85 (N = 286) Construct validity: used PCFA, explained variance: 35.79% Internal consistency Total: .78 Planning: .73 Self-assessment: .64 Search for human resources .57 (N = 30) Content validity: 2 rounds of Delphi study; Construct validity: used PCFA with varimax rotation, explained variance 36.4% Cronbach’s a .924 (total), .857 (SM), .847 (DL), .830 (SC) (N = 201) Content validity: 2 rounds of Delphi study; Construct validity: used a known-groups technique. Cronbach’s a coefficient .71–.79 (N = 30, 15 first year and 15 final year students)
S.-F. Cheng et al. / International Journal of Nursing Studies 47 (2010) 1152–1158
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Table 2 Phases and steps of the Self-Directed Learning Instrument (SDLI) development process. Process
Purpose
Methods/data
Phase I Step 1
Develop a new instrument for measurement of SDL Assemble 5 published SDL tools
Literature review Incorporate items from 5 existing SDL tools Assess and identify items
Step 2
Develop preliminary items for the new instrument
Phase II Step 1 Step 2
Test content validity Conduct Delphi study Assess the appropriateness, representativeness and explicitness of the SDLI’s (1st version) items and content
Step 3
Assess the appropriateness, representativeness, explicitness of the revised SDLI’s (2nd version) items and content
The 2nd round of Delphi study (N = 16)
Test the construct validity of the SDLI (3rd version) Model 1 Model 2 Model 3
Confirmatory factor analysis (CFA) Domains not correlated (N = 1072) Domains correlated Item deleted and domains correlated
Test the construct validity of the 4th version, model 4
Added 2 error covariances (N = 1072)
Test the internal consistency and reliability of the 4th version of SDLI (the final version)
Cronbach’s a N = 1072
Phase III Step 1 Step 2 Step 3
Step 4
Phase IV
Form an expert panel 1st round of Delphi study (N = 16)
Resulting Domains and Items 20 domains, 238 items 1st version: 6 domains, 55 items
2nd version: 4 domains, 31 items (retained 18 items, deleted 30 items, modified 7 items, added 6 items) 3rd version: 4 domains, 32 items (retained 30 items, split one item into 2) 4 domains, 32 items Model poor fit Model fair fit 4th version: 4 domains, 20 items (deleted 12 items) Model better fit 4 domains, 20 items Model good fit Total scale: .916 Domain 1: .801 Domain 2: .861 Domain 3: .785 Domain 4: .765
All five tools used an exploratory analysis method, principle component factor analysis and a known-group technique, to support the construct validity of the tool; therefore, different findings were expected. Only the instruments of Fisher et al. (2001) and Williamson (2007) have been tested in nursing students.
scale revision required; 3 = relevant but in need of small adjustments; and 4 = relevant, but needs rewording; 5 = relevant, clear and precise). Items with a mean score of 4.0 or above were retained. The decision to delete items scoring below 4.0 was made by the researchers based on the experts’ opinions.
2. Methodology
2.3. Phase III
This project of developing a Self-Directed Learning Instrument (SDLI) was conducted in four phases (Table 2).
The factor structure of the instrument was tested with confirmatory factor analysis (CFA). Two universities with three nursing programs (5-year ADN program, 4-year BSN program and 2-year RN-to-BSN program) in Taiwan were asked to participate in this study. The use of human subjects was approved by the Institutional Review Board (IRB) of the universities. A convenience sample of 1072 nursing students was recruited. All subjects were full time students. Students in the ADN program enter at the age of 15, after graduating from junior high school. Students in the 4-year BSN program enter at age 18, after graduating from senior high school. Students in the RN-to-BSN program enter at age 20–22, after graduating from the ADN program. The majority of the students were female (92%). CFA was performed to assess the structure of the instrument and identify the optimal model. Statistical analyses were performed using STATISTICA software, version 7.0.
2.1. Phase I The authors searched for SDL-related instruments in the OVID databases, bibliographies, and article references, and compiled a list of SDL items. 2.2. Phase II A Delphi study was conducted in two rounds. Sixteen experts were invited to participate in the Delphi study, including 6 experts in adult/higher education and 10 experts in nursing education. Each expert was asked to individually and independently evaluate and score each SDL item from Phase I for its appropriateness (the item can be used to measure student’s SDL), representativeness (the item expresses a core concept of SDL, according to the expert’s own understanding and interpretation of SDL) and explicitness (the item is clearly stated and easy to understand) using a 5-point Likert scale (1 = irrelevant and should be deleted; 2 = seemingly relevant but large-
2.4. Phase IV Finally, the internal consistency and reliability of the instrument were tested.
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Table 3 Goodness of fit statistics for comparative models of the SDLI.
Model Model Model Model
1 2 3 4
X2
df
p
RMSEA
RMS
GFI
AGFI
NNFI
NFI
AIC
4262.06 2624.39 778.10 695.88
464 458 164 161
.00 .00 .00 .00
.098 .075 .061 .057
.23 .06 .04 .04
.77 .84 .93 .94
.73 .81 .91 .92
.68 .81 .91 .92
.67 .80 .91 .93
4.484 2.824 .852 .763
Model 1: 4 factors. Model 2: 4 factors, correlated factors. Model 3: 4 factors, deleted items, correlated factors. (Items deleted: 2, 3, 6, 7, 17, 18, 22, 24, 25, 26, 28, 30). Model 4: 4 factors, deleted items, correlated factors, 2 error covariances (I4 & I5, I31 and I32). Note. RMSEA = Root Mean Squared Error of Approximation; RMS = standardized residual, GFI = the Goodness of Fit Index; AGFI = Adjusted Goodness of Fit Index; NNFI = Non-Normed Fit Index; NFI = Normed Fit Index; AIC = the Akaike Information Criterion.
3. Results 3.1. Phase I In the first phase of developing a Self-Directed Learning Instrument, the researchers reviewed the content of the five existing SDL instruments in the literature, counting a total of 238 items across 20 domains. Items with similar meanings and items deemed irrelevant to SDL were then deleted, resulting in 55 retained items across the following 6 domains: learning needs, learning motivation, learning skills, learning action, self-management, and self evaluation. 3.2. Phase II Phase II began with a 55-item preliminary instrument and ended with a 32-item instrument after a two-round Delphi study. In the first round, 30 items were deleted because of redundant or similar meanings; agreement was reached for 18 items; and 7 items were modified. One expert strongly recommended adding items related to interpersonal communication skills to the SDLI, arguing that the ability to interact with others is an important part of nursing students’ lifelong learning ability. Thus, six items related to interpersonal communication were added. After this initial critical review, the SDLI now contained 4 domains with 31 items. The researchers renamed these 4 domains as follows: learning motivation, planning and implementing, self-monitoring, and interpersonal communication. The SDLI was then provided to the same panel of experts for the 2nd round of Delphi study. The results showed agreement among the experts for 4 domains and 30 items. One item was identified as containing two meanings, so the researchers split it into two items. Thus, by now the SDLI had 4 domains with 32 items, and this version was used in the next phase for testing construct validity. 3.3. Phase III A 32-item SDLI was assessed using CFA. Four models were tested (Table 3). In model 2, the results showed model misfit. Examination of the wording and meaning of items was reviewed. Twelve items, including 5 negative statements, were discarded due to redundancy or vagueness. The remaining 20 items with a four-factor framework were tested in models 3 and 4.
The findings of model 4 represented a good fit to the model as indicated by the Root Mean Squared Error of Approximation (RMSEA), the RMS (standardized residual), the Goodness of Fit Index (GFI), Adjusted Goodness of Fit Index (AGFI), Non-Normed Fit Index (NNFI), Normed Fit Index (NFI) and the Akaike Information Criterion (AIC). The X2 values for these models remained significant, probably due to the large sample size and small discrepancies. The values of RMSEA, RMS, GFI, AGFI, NNFI, and NFI in model 4 supported the acceptable fit of the model. Thus, model 4 was the final model tested for the SDLI. Using maximum likelihood estimation, the factor loadings for each item were demonstrated to be greater than .40, with the exception of one item (.39). This also indicated that the latent variable can be measured by the items. The correlation coefficients among the four latent variables (four domains) ranged from .50 to .80 (Fig. 1). The error variances of the items were between .24 and .41, and no negative error variance or large error variances appeared. 3.4. Phase IV The last phase involved testing the internal consistency of each domain. The value of Cronbach’s a for the total item pool (N = 1072) was .916, and for the four domains were .801, .861, .785, and .765, respectively. The final SDLI contains 20 items across the 4 domains of learning motivation, planning and implementing, self-monitoring, and interpersonal communication (Appendix A). Learning motivation is defined as the inner drive of the learner as well as external stimuli that drive the desire to learn and to take responsibility for one’s learning. Planning and implementing is defined as the ability to independently set learning objectives, and to use appropriate learning strategies and resources in order to effectively achieve learning goals. Self-monitoring is defined as the ability to evaluate one’s learning process and outcomes, and to make progress. Interpersonal communication is defined as the ability of learners to interact with others to promote their own learning. This pencil–paper instrument takes around 10 min to complete. All items of SDLI are positively stated. The respondent is asked to rate each item on a 5-point Likert scale ranging from 1 for ‘‘strongly disagree’’ to 5 for ‘‘strongly agree’’. Thus, the total possible score on the SDLI ranges from 20 to 100. In this study, the students’ overall mean score as measured by the SDLI was 3.60, which implied that their
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S.-F. Cheng et al. / International Journal of Nursing Studies 47 (2010) 1152–1158
Fig. 1. Measurement model of the SDLI.
SDL abilities were moderate. The mean scores of the students in the 5-year AND program, 4-year BSN program, and 2-year RN to BSN program were 3.52, 3.59 and 3.7, respectively. The highest mean score (X = 3.74) of the four domains was ‘‘interpersonal communication’’ and the lowest score (X = 3.45) was ‘‘planning and implementing’’. The students’ SDL ability in the 2-year RN to BSN program was significantly higher than the other two programs (F = 10.47, p = .000). 4. Discussion and conclusion As shown in the literature, evaluating the psychometric properties of existing SDL tools has produced mixed findings. This is probably because those instruments were developed using exploratory analysis method. By contrast, the SDLI in this study was developed using confirmatory factor analysis, which verified the framework of SDL. In addition, this study is unique because the sample is taken from three different types of nursing programs from two
schools, a public college in the north and a private university in southern Taiwan. Hence, this study’s SDLI appears to have greater generalizability and validity than currently available measurement tools. It is hoped that the instrument developed in this study can eventually help nursing educators better understand students’ SDL abilities and implement appropriate teaching strategies, such as problem-based learning. In the literature, the application of problem-based learning in pedagogy has been shown to enhance the SDL ability of nursing students, and thereby develop their capacity to engage in lifelong learning (Kocaman et al., 2009). Both teachers and students can use the SDLI in every year of nursing training to identify learning obstacles and seek relevant counseling and support. This instrument reflects the situation of two universities in Taiwan. Future studies may use the SDLI to explore the SDL abilities of students across different programs, schools, regions and cultures. The data collected from this study may also be used to develop a pedagogy and curriculum aimed at enhancing students’ SDL abilities.
S.-F. Cheng et al. / International Journal of Nursing Studies 47 (2010) 1152–1158
Acknowledgements The researchers would like to thank Taiwan National Science Council for the grant NSC97-2511-S-227-006 that enabled this study, and our students for their unfailing patience and openness.
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Conflict of interest: None declared. Funding: The research funding (NT$ 730,000) was sponsored by Taiwan National Science Council. Ethical Approval: National Taipei College of Nursing. The reference number is 98A208.
Appendix A. Self-Directed Learning Instrument (SDLI) for Nursing Students Directions: Please read each statement and circle the number that best describes your thoughts and feelings about your own learning. There is no right or wrong answer. 5 = Strongly agree, 4 = Agree, 3 = Neutral, 2 = Disagree, 1 = Strongly disagree 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
I know what I need to learn. Regardless of the results or effectiveness of my learning, I still like learning. I strongly hope to constantly improve and excel in my learning. My successes and failures inspire me to continue learning. I enjoy finding answers to questions. I will not give up learning because I face some difficulties. I can pro-actively establish my learning goals. I know what learning strategies are appropriate for me in reaching my learning goals. I set the priorities of my learning. Whether in the clinical practicum, classroom or on my own, I am able to follow my own plan of learning. I am good at arranging and controlling my learning time. I know how to find resources for my learning. I can connect new knowledge with my own personal experiences. I understand the strengths and weakness of my learning. I can monitor my learning progress. I can evaluate on my own my learning outcomes. My interaction with others helps me plan for further learning. I would like to learn the language and culture of those whom I frequently interact with. I am able to express messages effectively in oral presentations. I am able to communicate messages effectively in writing.
5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5
4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
Original SDLI in Chinese version.
1
5
4
3
2
1
2
5
4
3
2
1
3
5
4
3
2
1
4
5
4
3
2
1
5
5
4
3
2
1
6
5
4
3
2
1
7
5
4
3
2
1
8
5
4
3
2
1
9
5
4
3
2
1
10
5
4
3
2
1
11
5
4
3
2
1
12
5
4
3
2
1
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S.-F. Cheng et al. / International Journal of Nursing Studies 47 (2010) 1152–1158
13
5
4
3
2
1
14
5
4
3
2
1
15
5
4
3
2
1
16
5
4
3
2
1
17
5
4
3
2
1
18
5
4
3
2
1
19
5
4
3
2
1
20
5
4
3
2
1
References American Association of Colleges of Nursing, 2008. The Essentials of Baccalaureate Education for Professional Nursing Practice. American Association of Colleges of Nursing. Brookfield, S., 1986. Understanding and Facilitating Adult Learning. Jossey-Bass, San Francisco. Cameron, D.R., 1997. Self-directed learning: toward a comprehensive model. Adult Education Quarterly 48 (1), 18–33. Deng, Y.L., 1995. Adult Teaching and Self-directed Learning. Wu-Nan, Taipei (in Chinese). Fisher, M., King, J., Tague, G., 2001. Development of a self-directed learning readiness scale for nursing education. Nurse Education Today 21 (7), 516–525. Greg, R., 1993. Student perceptions about self-directed learning in a professional course implementing problem-based learning. Studies in Higher Education 18 (1), 53–63.
Guglielmino, L.M., 1977. Development of the self-directed learning readiness scale. Unpublished Doctoral Dissertation. University of Georgia. Dissertation Abstracts International 38, 6467A. Ho, C.R., 1998. Facilitation to self-directed learning: a refection of teaching experiment on contract learning. National Science Council Journal: Humanity and Social Sciences 8 (3), 417–426 (in Chinese). Knowles, M., 1975. Self-Directed Learning: a Guide for Learners and Teachers. Association Press, New York. Kocaman, G., Dicle, A., Ugur, A., 2009. A longitudinal analysis of the selfdirected learning readiness level of nursing students enrolled in a problem-based curriculum. Journal of Nursing Education 48 (5), 286– 290. Williamson, S.N., 2007. Development of a self-rating scale of self-directed learning. Nurse Researcher 14 (2), 66–83.
Contents lists available at ScienceDirect
International Journal of Nursing Studies journal homepage: www.elsevier.com/ijns
Development and preliminary testing of a self-rating instrument to measure self-directed learning ability of nursing students Su-Fen Cheng a, Chien-Lin Kuo b, Kuan-Chia Lin a, Jane Lee-Hsieh a,* a b
School of Nursing, National Taipei College of Nursing, 365, Ming-Te Rd, Peitou District, Taipei 11219, Taiwan, ROC Department of Nursing, Fooyin University, Kaohsiung, Taiwan, ROC
A R T I C L E I N F O
A B S T R A C T
Article history: Received 21 August 2009 Received in revised form 12 January 2010 Accepted 7 February 2010
Background: With the growing trend of preparing students for lifelong learning, the theory of self-directed learning (SDL) has been increasingly applied in the context of higher education. In order to foster lifelong learning, abilities among nursing students, faculties need to have an appropriate instrument to measure the SDL abilities of nursing students. Objectives: The objectives of this study were to develop an instrument to measure the SDL abilities of nursing students and to test the validity and reliability of this instrument. Methods: This study was conducted in 4 phases. In Phase 1, based on a review of the literature, the researchers developed an instrument to measure SDL. In Phase 2, two rounds of the Delphi study were conducted, to determine the content validity of the instrument. In Phase 3, a convenience sample of 1072 nursing students from two representative schools across three different types of nursing programs were recruited to test the construct validity of the Self-Directed Learning Instrument (SDLI). Finally, in Phase 4, the internal consistency and reliability of the instrument were tested. Results: The resulting SDLI consists of 20 items across the following four domains: learning motivation, planning and implementing, self-monitoring, and interpersonal, communication. The final model in confirmatory factor analysis revealed that this 20-item SDLI indicated a good fit of the model. The value of Cronbach’s a for the total scale was .916 and for the four domains were .801, .861, .785, and .765, respectively. Conclusions: The SDLI is a valid and reliable instrument for identifying student SDL abilities. It is available to students in nursing and similar medical programs to evaluate their own SDL. This scale may also enable nursing faculty to assess students’ SDL status, design better lesson plans and curricula, and, implement appropriate teaching strategies for nursing students in order to foster the growth of lifelong learning abilities. ß 2010 Elsevier Ltd. All rights reserved.
Keywords: Confirmatory factor analysis Delphi study Instrument development Nursing students Self-directed learning
What is already known about the topic? A key factor affecting lifelong learning abilities is whether students have the ability to engage in selfdirected learning (SDL). There currently exist five instruments measuring SDL. However, evaluations of their psychometric properties
* Corresponding author. Tel.: +886 2 28227101x3199; fax: +886 2 28213233. E-mail address: [email protected] (J. Lee-Hsieh). 0020-7489/$ – see front matter ß 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.ijnurstu.2010.02.002
have produced mixed findings. This is probably because most of these instruments were developed using exploratory analysis. Thus far, these instruments have only been analyzed for their content and factor domains, and have not been tested for their fit with the theory. What this paper adds A Self-Directed Learning Instrument (SDLI) specifically developed and tested for nursing education, across different programs and grades.
S.-F. Cheng et al. / International Journal of Nursing Studies 47 (2010) 1152–1158
The SDLI is a reliable and valid instrument that measures four domains of SDL: learning motivation, planning and implementing, self-monitoring, and interpersonal communication. This study provides new empirical evidence and verifies the structure of the core concept of SDL. It matches empirical evidence to the theory.
1. Introduction There is a growing trend of preparing students for lifelong learning. In the field of nursing, students enter the field with extensive professional training, but must also be able to constantly update their knowledge through selfdirected learning (SDL). Thus, teaching SDL skills to nursing students helps to prepare them for success in their future careers, and enables them to engage in lifelong learning. To facilitate the development of SDL skills in nursing students, a valid and reliable tool should be made available to nursing schools to enable them to measure the SDL abilities of nursing students. Thus, the purposes of this study were (1) to develop an instrument to measure the SDL ability of nursing students and (2) to test the validity and reliability of this instrument. 1.1. Concepts of SDL According to Knowles (1975), self-directed learning is ‘‘a process in which individuals take the initiative, with or without the help of others, in diagnosing their learning needs, formulating learning goals, identifying human and material resources for learning, choosing and implement-
1153
ing appropriate learning strategies, and evaluating learning outcomes’’ (p. 18). Brookfield (1986) provided a similar definition of SDL. Greg (1993) argued that self-directed learners should have the ability to collaborate with peers, and see peers as learning resources. Cameron (1997) stated that a comprehensive model for SDL should involve selfmanagement, self-monitoring, and motivation. The American Association of Colleges of Nursing (2008) emphasizes the importance of communication skills in developing Baccalaureate programs and suggests that nursing faculty should design learning activities that focus on practicing communication. Based on the above discussion, the process of SDL covers the following domains: learning needs or learning motivation, learning resources, learning goals, learning plans and activities, learning evaluation, and communication skills. 1.2. Overview of existing SDL instruments The researchers used the OVID databases, bibliographies, and article references to search for existing SDL instruments. Only five instruments that directly measured SDL were found. These included Guglielmino’s (1977) SDL readiness scale, Deng’s (1995) Chinese version of Guglielmino’s instrument, Ho’s (1998) SDL ability scale, Fisher, King, and Tague’s (2001) SDL readiness scale, and Williamson’s (2007) self-rating scale of SDL. Descriptions and psychometric indices are presented in Table 1. The components of these SDL tools include: effective learning, learning motivation, active learning, independent learning, creative learning, self-management, desire for learning, self-control, evaluation, and interpersonal skills. The number of items ranged from 14 to 65.
Table 1 Reliability and validity of existing SDL instruments. Instrument
Description
Psychometric indices
Guglielmino (1977) Self-directed learning readiness scale
Defined 8 components of SDL (openness to learning opportunities, self-concept as an effective learner, initiative and independence in learning, informed acceptance of responsibility for one’s own learning, love of learning, creativity, positive orientation to the future, ability to use basic study skills, and problem-solving skills); Total items: 58 items Adapted from Guglielmino’s instrument and categorized 6 components (effective learning, love of learning, learning motivation, active learning, independent learning, and creative learning); Total items: 58 items 3 domains (planning: 6 items; self-assessment: 5 items; search for human resources: 3 items); Total items: 14
Content validity: Delphi study Construct validity: used Principle component factor analysis (PCFA), explained variance: 48%
Deng (1995) Chinese version of Guglielmino’s self-directed learning readiness scale Ho (1998) Self-directed ability scale (in Chinese)
Fisher et al. (2001) Self-directed learning readiness scale
3 components (self-management, desire for learning, and self-control); Total items: 40
Williamson (2007) Self-rating scale of self-directed learning
5 components (awareness, learning strategies, learning activities, evaluation, and interpersonal skills); Total item: 65
Translate validity Construct validity: used PCFA varimax rotation, explained variance: 89.75% Cronbach’s a .64–.85 (N = 286) Construct validity: used PCFA, explained variance: 35.79% Internal consistency Total: .78 Planning: .73 Self-assessment: .64 Search for human resources .57 (N = 30) Content validity: 2 rounds of Delphi study; Construct validity: used PCFA with varimax rotation, explained variance 36.4% Cronbach’s a .924 (total), .857 (SM), .847 (DL), .830 (SC) (N = 201) Content validity: 2 rounds of Delphi study; Construct validity: used a known-groups technique. Cronbach’s a coefficient .71–.79 (N = 30, 15 first year and 15 final year students)
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Table 2 Phases and steps of the Self-Directed Learning Instrument (SDLI) development process. Process
Purpose
Methods/data
Phase I Step 1
Develop a new instrument for measurement of SDL Assemble 5 published SDL tools
Literature review Incorporate items from 5 existing SDL tools Assess and identify items
Step 2
Develop preliminary items for the new instrument
Phase II Step 1 Step 2
Test content validity Conduct Delphi study Assess the appropriateness, representativeness and explicitness of the SDLI’s (1st version) items and content
Step 3
Assess the appropriateness, representativeness, explicitness of the revised SDLI’s (2nd version) items and content
The 2nd round of Delphi study (N = 16)
Test the construct validity of the SDLI (3rd version) Model 1 Model 2 Model 3
Confirmatory factor analysis (CFA) Domains not correlated (N = 1072) Domains correlated Item deleted and domains correlated
Test the construct validity of the 4th version, model 4
Added 2 error covariances (N = 1072)
Test the internal consistency and reliability of the 4th version of SDLI (the final version)
Cronbach’s a N = 1072
Phase III Step 1 Step 2 Step 3
Step 4
Phase IV
Form an expert panel 1st round of Delphi study (N = 16)
Resulting Domains and Items 20 domains, 238 items 1st version: 6 domains, 55 items
2nd version: 4 domains, 31 items (retained 18 items, deleted 30 items, modified 7 items, added 6 items) 3rd version: 4 domains, 32 items (retained 30 items, split one item into 2) 4 domains, 32 items Model poor fit Model fair fit 4th version: 4 domains, 20 items (deleted 12 items) Model better fit 4 domains, 20 items Model good fit Total scale: .916 Domain 1: .801 Domain 2: .861 Domain 3: .785 Domain 4: .765
All five tools used an exploratory analysis method, principle component factor analysis and a known-group technique, to support the construct validity of the tool; therefore, different findings were expected. Only the instruments of Fisher et al. (2001) and Williamson (2007) have been tested in nursing students.
scale revision required; 3 = relevant but in need of small adjustments; and 4 = relevant, but needs rewording; 5 = relevant, clear and precise). Items with a mean score of 4.0 or above were retained. The decision to delete items scoring below 4.0 was made by the researchers based on the experts’ opinions.
2. Methodology
2.3. Phase III
This project of developing a Self-Directed Learning Instrument (SDLI) was conducted in four phases (Table 2).
The factor structure of the instrument was tested with confirmatory factor analysis (CFA). Two universities with three nursing programs (5-year ADN program, 4-year BSN program and 2-year RN-to-BSN program) in Taiwan were asked to participate in this study. The use of human subjects was approved by the Institutional Review Board (IRB) of the universities. A convenience sample of 1072 nursing students was recruited. All subjects were full time students. Students in the ADN program enter at the age of 15, after graduating from junior high school. Students in the 4-year BSN program enter at age 18, after graduating from senior high school. Students in the RN-to-BSN program enter at age 20–22, after graduating from the ADN program. The majority of the students were female (92%). CFA was performed to assess the structure of the instrument and identify the optimal model. Statistical analyses were performed using STATISTICA software, version 7.0.
2.1. Phase I The authors searched for SDL-related instruments in the OVID databases, bibliographies, and article references, and compiled a list of SDL items. 2.2. Phase II A Delphi study was conducted in two rounds. Sixteen experts were invited to participate in the Delphi study, including 6 experts in adult/higher education and 10 experts in nursing education. Each expert was asked to individually and independently evaluate and score each SDL item from Phase I for its appropriateness (the item can be used to measure student’s SDL), representativeness (the item expresses a core concept of SDL, according to the expert’s own understanding and interpretation of SDL) and explicitness (the item is clearly stated and easy to understand) using a 5-point Likert scale (1 = irrelevant and should be deleted; 2 = seemingly relevant but large-
2.4. Phase IV Finally, the internal consistency and reliability of the instrument were tested.
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Table 3 Goodness of fit statistics for comparative models of the SDLI.
Model Model Model Model
1 2 3 4
X2
df
p
RMSEA
RMS
GFI
AGFI
NNFI
NFI
AIC
4262.06 2624.39 778.10 695.88
464 458 164 161
.00 .00 .00 .00
.098 .075 .061 .057
.23 .06 .04 .04
.77 .84 .93 .94
.73 .81 .91 .92
.68 .81 .91 .92
.67 .80 .91 .93
4.484 2.824 .852 .763
Model 1: 4 factors. Model 2: 4 factors, correlated factors. Model 3: 4 factors, deleted items, correlated factors. (Items deleted: 2, 3, 6, 7, 17, 18, 22, 24, 25, 26, 28, 30). Model 4: 4 factors, deleted items, correlated factors, 2 error covariances (I4 & I5, I31 and I32). Note. RMSEA = Root Mean Squared Error of Approximation; RMS = standardized residual, GFI = the Goodness of Fit Index; AGFI = Adjusted Goodness of Fit Index; NNFI = Non-Normed Fit Index; NFI = Normed Fit Index; AIC = the Akaike Information Criterion.
3. Results 3.1. Phase I In the first phase of developing a Self-Directed Learning Instrument, the researchers reviewed the content of the five existing SDL instruments in the literature, counting a total of 238 items across 20 domains. Items with similar meanings and items deemed irrelevant to SDL were then deleted, resulting in 55 retained items across the following 6 domains: learning needs, learning motivation, learning skills, learning action, self-management, and self evaluation. 3.2. Phase II Phase II began with a 55-item preliminary instrument and ended with a 32-item instrument after a two-round Delphi study. In the first round, 30 items were deleted because of redundant or similar meanings; agreement was reached for 18 items; and 7 items were modified. One expert strongly recommended adding items related to interpersonal communication skills to the SDLI, arguing that the ability to interact with others is an important part of nursing students’ lifelong learning ability. Thus, six items related to interpersonal communication were added. After this initial critical review, the SDLI now contained 4 domains with 31 items. The researchers renamed these 4 domains as follows: learning motivation, planning and implementing, self-monitoring, and interpersonal communication. The SDLI was then provided to the same panel of experts for the 2nd round of Delphi study. The results showed agreement among the experts for 4 domains and 30 items. One item was identified as containing two meanings, so the researchers split it into two items. Thus, by now the SDLI had 4 domains with 32 items, and this version was used in the next phase for testing construct validity. 3.3. Phase III A 32-item SDLI was assessed using CFA. Four models were tested (Table 3). In model 2, the results showed model misfit. Examination of the wording and meaning of items was reviewed. Twelve items, including 5 negative statements, were discarded due to redundancy or vagueness. The remaining 20 items with a four-factor framework were tested in models 3 and 4.
The findings of model 4 represented a good fit to the model as indicated by the Root Mean Squared Error of Approximation (RMSEA), the RMS (standardized residual), the Goodness of Fit Index (GFI), Adjusted Goodness of Fit Index (AGFI), Non-Normed Fit Index (NNFI), Normed Fit Index (NFI) and the Akaike Information Criterion (AIC). The X2 values for these models remained significant, probably due to the large sample size and small discrepancies. The values of RMSEA, RMS, GFI, AGFI, NNFI, and NFI in model 4 supported the acceptable fit of the model. Thus, model 4 was the final model tested for the SDLI. Using maximum likelihood estimation, the factor loadings for each item were demonstrated to be greater than .40, with the exception of one item (.39). This also indicated that the latent variable can be measured by the items. The correlation coefficients among the four latent variables (four domains) ranged from .50 to .80 (Fig. 1). The error variances of the items were between .24 and .41, and no negative error variance or large error variances appeared. 3.4. Phase IV The last phase involved testing the internal consistency of each domain. The value of Cronbach’s a for the total item pool (N = 1072) was .916, and for the four domains were .801, .861, .785, and .765, respectively. The final SDLI contains 20 items across the 4 domains of learning motivation, planning and implementing, self-monitoring, and interpersonal communication (Appendix A). Learning motivation is defined as the inner drive of the learner as well as external stimuli that drive the desire to learn and to take responsibility for one’s learning. Planning and implementing is defined as the ability to independently set learning objectives, and to use appropriate learning strategies and resources in order to effectively achieve learning goals. Self-monitoring is defined as the ability to evaluate one’s learning process and outcomes, and to make progress. Interpersonal communication is defined as the ability of learners to interact with others to promote their own learning. This pencil–paper instrument takes around 10 min to complete. All items of SDLI are positively stated. The respondent is asked to rate each item on a 5-point Likert scale ranging from 1 for ‘‘strongly disagree’’ to 5 for ‘‘strongly agree’’. Thus, the total possible score on the SDLI ranges from 20 to 100. In this study, the students’ overall mean score as measured by the SDLI was 3.60, which implied that their
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Fig. 1. Measurement model of the SDLI.
SDL abilities were moderate. The mean scores of the students in the 5-year AND program, 4-year BSN program, and 2-year RN to BSN program were 3.52, 3.59 and 3.7, respectively. The highest mean score (X = 3.74) of the four domains was ‘‘interpersonal communication’’ and the lowest score (X = 3.45) was ‘‘planning and implementing’’. The students’ SDL ability in the 2-year RN to BSN program was significantly higher than the other two programs (F = 10.47, p = .000). 4. Discussion and conclusion As shown in the literature, evaluating the psychometric properties of existing SDL tools has produced mixed findings. This is probably because those instruments were developed using exploratory analysis method. By contrast, the SDLI in this study was developed using confirmatory factor analysis, which verified the framework of SDL. In addition, this study is unique because the sample is taken from three different types of nursing programs from two
schools, a public college in the north and a private university in southern Taiwan. Hence, this study’s SDLI appears to have greater generalizability and validity than currently available measurement tools. It is hoped that the instrument developed in this study can eventually help nursing educators better understand students’ SDL abilities and implement appropriate teaching strategies, such as problem-based learning. In the literature, the application of problem-based learning in pedagogy has been shown to enhance the SDL ability of nursing students, and thereby develop their capacity to engage in lifelong learning (Kocaman et al., 2009). Both teachers and students can use the SDLI in every year of nursing training to identify learning obstacles and seek relevant counseling and support. This instrument reflects the situation of two universities in Taiwan. Future studies may use the SDLI to explore the SDL abilities of students across different programs, schools, regions and cultures. The data collected from this study may also be used to develop a pedagogy and curriculum aimed at enhancing students’ SDL abilities.
S.-F. Cheng et al. / International Journal of Nursing Studies 47 (2010) 1152–1158
Acknowledgements The researchers would like to thank Taiwan National Science Council for the grant NSC97-2511-S-227-006 that enabled this study, and our students for their unfailing patience and openness.
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Conflict of interest: None declared. Funding: The research funding (NT$ 730,000) was sponsored by Taiwan National Science Council. Ethical Approval: National Taipei College of Nursing. The reference number is 98A208.
Appendix A. Self-Directed Learning Instrument (SDLI) for Nursing Students Directions: Please read each statement and circle the number that best describes your thoughts and feelings about your own learning. There is no right or wrong answer. 5 = Strongly agree, 4 = Agree, 3 = Neutral, 2 = Disagree, 1 = Strongly disagree 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
I know what I need to learn. Regardless of the results or effectiveness of my learning, I still like learning. I strongly hope to constantly improve and excel in my learning. My successes and failures inspire me to continue learning. I enjoy finding answers to questions. I will not give up learning because I face some difficulties. I can pro-actively establish my learning goals. I know what learning strategies are appropriate for me in reaching my learning goals. I set the priorities of my learning. Whether in the clinical practicum, classroom or on my own, I am able to follow my own plan of learning. I am good at arranging and controlling my learning time. I know how to find resources for my learning. I can connect new knowledge with my own personal experiences. I understand the strengths and weakness of my learning. I can monitor my learning progress. I can evaluate on my own my learning outcomes. My interaction with others helps me plan for further learning. I would like to learn the language and culture of those whom I frequently interact with. I am able to express messages effectively in oral presentations. I am able to communicate messages effectively in writing.
5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5
4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
Original SDLI in Chinese version.
1
5
4
3
2
1
2
5
4
3
2
1
3
5
4
3
2
1
4
5
4
3
2
1
5
5
4
3
2
1
6
5
4
3
2
1
7
5
4
3
2
1
8
5
4
3
2
1
9
5
4
3
2
1
10
5
4
3
2
1
11
5
4
3
2
1
12
5
4
3
2
1
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13
5
4
3
2
1
14
5
4
3
2
1
15
5
4
3
2
1
16
5
4
3
2
1
17
5
4
3
2
1
18
5
4
3
2
1
19
5
4
3
2
1
20
5
4
3
2
1
References American Association of Colleges of Nursing, 2008. The Essentials of Baccalaureate Education for Professional Nursing Practice. American Association of Colleges of Nursing. Brookfield, S., 1986. Understanding and Facilitating Adult Learning. Jossey-Bass, San Francisco. Cameron, D.R., 1997. Self-directed learning: toward a comprehensive model. Adult Education Quarterly 48 (1), 18–33. Deng, Y.L., 1995. Adult Teaching and Self-directed Learning. Wu-Nan, Taipei (in Chinese). Fisher, M., King, J., Tague, G., 2001. Development of a self-directed learning readiness scale for nursing education. Nurse Education Today 21 (7), 516–525. Greg, R., 1993. Student perceptions about self-directed learning in a professional course implementing problem-based learning. Studies in Higher Education 18 (1), 53–63.
Guglielmino, L.M., 1977. Development of the self-directed learning readiness scale. Unpublished Doctoral Dissertation. University of Georgia. Dissertation Abstracts International 38, 6467A. Ho, C.R., 1998. Facilitation to self-directed learning: a refection of teaching experiment on contract learning. National Science Council Journal: Humanity and Social Sciences 8 (3), 417–426 (in Chinese). Knowles, M., 1975. Self-Directed Learning: a Guide for Learners and Teachers. Association Press, New York. Kocaman, G., Dicle, A., Ugur, A., 2009. A longitudinal analysis of the selfdirected learning readiness level of nursing students enrolled in a problem-based curriculum. Journal of Nursing Education 48 (5), 286– 290. Williamson, S.N., 2007. Development of a self-rating scale of self-directed learning. Nurse Researcher 14 (2), 66–83.