Anatomy Education Environment Measurement Inventory: A Valid Tool to Measure the Anatomy Learning Environment
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| Title: | Anatomy Education Environment Measurement Inventory: A Valid Tool to Measure the Anatomy Learning Environment |
|---|---|
| Language: | English |
| Authors: | Hadie, Siti Nurma Hanim (ORCID |
| Source: | Anatomical Sciences Education. Sep-Oct 2017 10(5):423-432. |
| Availability: | Wiley-Blackwell. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA |
| Peer Reviewed: | Y |
| Page Count: | 10 |
| Publication Date: | 2017 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Higher Education |
| Descriptors: | Anatomy, Educational Environment, Measures (Individuals), Delphi Technique, Student Attitudes, Medical Students, Medical Schools, Foreign Countries, Content Validity, Test Reliability, Factor Analysis, Goodness of Fit, Psychometrics |
| Geographic Terms: | Malaysia |
| DOI: | 10.1002/ase.1683 |
| ISSN: | 1935-9772 |
| Abstract: | Students' perceptions of the education environment influence their learning. Ever since the major medical curriculum reform, anatomy education has undergone several changes in terms of its curriculum, teaching modalities, learning resources, and assessment methods. By measuring students' perceptions concerning anatomy education environment, valuable information can be obtained to facilitate improvements in teaching and learning. Hence, it is important to use a valid inventory that specifically measures attributes of the anatomy education environment. In this study, a new 11-factor, 132-items Anatomy Education Environment Measurement Inventory (AEEMI) was developed using Delphi technique and was validated in a Malaysian public medical school. The inventory was found to have satisfactory content evidence (scale-level content validity index [total] = 0.646); good response process evidence (scale-level face validity index [total] = 0.867); and acceptable to high internal consistency, with the Raykov composite reliability estimates of the six factors are in the range of 0.604-0.876. The best fit model of the AEEMI is achieved with six domains and 25 items (X[superscript 2] = 415.67, P < 0.001, ChiSq/df = 1.63, RMSEA = 0.045, GFI = 0.905, CFI = 0.937, NFI = 0.854, TLI = 0.926). Hence, AEEMI was proven to have good psychometric properties, and thus could be used to measure the anatomy education environment in Malaysia. A concerted collaboration should be initiated toward developing a valid universal tool that, using the methods outlined in this study, measures the anatomy education environment across different institutions and countries. |
| Abstractor: | As Provided |
| Entry Date: | 2017 |
| Accession Number: | EJ1153168 |
| Database: | ERIC |
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| FullText | Links: – Type: pdflink Url: https://content.ebscohost.com/cds/retrieve?content=AQICAHj0k_4E0hTGH8RJwT4gCJyBsGNe_WN95AvKlDbXJGqwxwF0MXaxtIsmHt02vAtZdbkAAAAA4TCB3gYJKoZIhvcNAQcGoIHQMIHNAgEAMIHHBgkqhkiG9w0BBwEwHgYJYIZIAWUDBAEuMBEEDOxKyjp0tm9NdSkKoAIBEICBmRosz06rgr5w3QBQs070KaXU4qSmTh4P6BbpSejm6rG-3UzKNbzz4ucXybKKBpWwvszmQ8CoyOKcxvKxlB9vXdxBKBX_g8sSprB-E7T3FVEzr89FL0qAWdv5bK9LxaiIj2k3nXNca65QYXnIxN8n81CdB7Tx8HcqTMU3ORVMMQ-TmK7fhIidU8x_U2H8qGlIJoKJtEQB33yiyw== Text: Availability: 1 Value: <anid>AN0124968752;[8z8k]01sep.17;2018Jun29.10:27;v2.2.500</anid> <title id="AN0124968752-1">Anatomy education environment measurement inventory: A valid tool to measure the anatomy learning environment. </title> <p>Students' perceptions of the education environment influence their learning. Ever since the major medical curriculum reform, anatomy education has undergone several changes in terms of its curriculum, teaching modalities, learning resources, and assessment methods. By measuring students' perceptions concerning anatomy education environment, valuable information can be obtained to facilitate improvements in teaching and learning. Hence, it is important to use a valid inventory that specifically measures attributes of the anatomy education environment. In this study, a new 11‐factor, 132‐items Anatomy Education Environment Measurement Inventory (AEEMI) was developed using Delphi technique and was validated in a Malaysian public medical school. The inventory was found to have satisfactory content evidence (scale‐level content validity index [total] = 0.646); good response process evidence (scale‐level face validity index [total] = 0.867); and acceptable to high internal consistency, with the Raykov composite reliability estimates of the six factors are in the range of 0.604–0.876. The best fit model of the AEEMI is achieved with six domains and 25 items (X2 = 415.67, P &lt; 0.001, ChiSq/df = 1.63, RMSEA = 0.045, GFI = 0.905, CFI = 0.937, NFI = 0.854, TLI = 0.926). Hence, AEEMI was proven to have good psychometric properties, and thus could be used to measure the anatomy education environment in Malaysia. A concerted collaboration should be initiated toward developing a valid universal tool that, using the methods outlined in this study, measures the anatomy education environment across different institutions and countries. Anat Sci Educ 10: 423–432. © 2017 American Association of Anatomists.</p> <p>anatomy education; medical students; learning environment; measurement inventory; educational climate; validity</p> <p>The educational “environment” or “climate” refers to any learning experience that influences students' motivation to learn, thereby affecting their attitudes, values, and behaviors related to a learning task (Roff and McAleer, [<reflink idref="bib67" id="ref1">67</reflink>] ; AMA, [<reflink idref="bib2" id="ref2">2</reflink>] ). A student may have high internal motivation to learn a subject, but a “demotivating” environment including such features as inadequate teaching resources or an uncomfortable class atmosphere could prompt students to disengage from the content of instruction, and this will negatively affect their learning (Hutchinson, [<reflink idref="bib36" id="ref3">36</reflink>] ). As clarified in Maslow's hierarchy of needs for motivating learning (Burleson and Thoron, [<reflink idref="bib17" id="ref4">17</reflink>] ), a good educational environment should comprise factors that can fulfill the students' physical needs (e.g., through being located in a comfortable lecture hall); make the students feel safe in conducting certain learning activities (e.g., through the provision of clear rules and regulations in class); instill a sense of “belonging” in students during learning (e.g., through opportunities to work with colleagues of a similar background); and boost students' self‐esteem (e.g., through constructive feedback after examination). When the four levels of the hierarchy are fulfilled, the students will be able to reach the final level, which is self‐actualization; this represents a state where the students become independent learners who have autonomous control over their learning (Burleson and Thoron, [<reflink idref="bib17" id="ref5">17</reflink>] ). Hence, a good educational environment is important for students' learning (Pimparyon et al., [<reflink idref="bib57" id="ref6">57</reflink>] ; Baeten et al., [<reflink idref="bib5" id="ref7">5</reflink>] ).</p> <p>In general, the educational environment comprises several factors, such as the culture and norms of an institution (e.g., rules and regulations), the curriculum (e.g., curriculum types, learning outcomes and assessment), teachers (e.g., teaching behavior, role modeling, and teaching ability), physical surroundings (e.g., lecture hall and teaching facilities), and the social environment (e.g., peer support, mentoring system, and after class consultation; Roff and McAleer, [<reflink idref="bib67" id="ref8">67</reflink>] ; Hutchinson, [<reflink idref="bib36" id="ref9">36</reflink>] ; AMA, [<reflink idref="bib2" id="ref10">2</reflink>] ). By evaluating how the students perceive these factors, unfavorable elements related to each factor can be modified to provide students with a better learning experience. Therefore, measuring the educational environment is an imperative action prior to any program evaluation and change, as this will provide valuable input on elements that might affect students' learning (Dent and Harden, [<reflink idref="bib24" id="ref11">24</reflink>] ).</p> <p>There are many instruments available to measure the educational environment (Roff et al., [<reflink idref="bib68" id="ref12">68</reflink>] ; Fraser, [<reflink idref="bib31" id="ref13">31</reflink>] ; Chan, [<reflink idref="bib18" id="ref14">18</reflink>] ). For instance, the educational environment related to the medical and allied health sciences field is commonly evaluated using the Dundee Ready Educational Environment Measure (DREEM; Roff et al., [<reflink idref="bib68" id="ref15">68</reflink>] ; Al‐Hazimi et al., [<reflink idref="bib1" id="ref16">1</reflink>] ; Varma et al., [<reflink idref="bib76" id="ref17">76</reflink>] ; Arzuman et al., [<reflink idref="bib4" id="ref18">4</reflink>] ; Yusoff et al., [<reflink idref="bib78" id="ref19">78</reflink>] ). Although the DREEM has profound psychometric credentials established across different cohorts of undergraduate students of medical and allied health sciences, however, the items in DREEM reflect general construct of educational environment, and thus they may not cover certain important factors of the educational environment in a specific discipline. Furthermore, it is known that elements of the educational environment can vary across classes and courses (Roff and McAleer, [<reflink idref="bib67" id="ref20">67</reflink>] ). For example, in anatomy education, different educational methods are needed when teaching different cohort of students to meet different learning outcomes (Estai and Bunt, [<reflink idref="bib29" id="ref21">29</reflink>] ).</p> <p>Evaluating the anatomy education environment requires additional information that is not addressed in DREEM. For instance, students' perceptions related to learning anatomy through dissection and using cadaveric specimens could be missed if DREEM is to be used as a measurement tool. Although cadaveric dissection is regarded as the “gold standard” method of learning anatomy by many anatomists (Parker, [<reflink idref="bib55" id="ref22">55</reflink>] ; Patel and Moxham, [<reflink idref="bib56" id="ref23">56</reflink>] ), arguments in the literature have also highlighted the disadvantages of cadaveric dissection (McLachlan and Patten, [<reflink idref="bib48" id="ref24">48</reflink>] ), as well as learning potential related to new teaching modalities for anatomy teaching (Collins, [<reflink idref="bib20" id="ref25">20</reflink>] ; Trelease, [<reflink idref="bib74" id="ref26">74</reflink>] ). Supporting this, a systematic review conducted by Winkelmann ([<reflink idref="bib77" id="ref27">77</reflink>] ) emphasized the lack of objective scientific evidence corroborating the view that cadaveric dissection is the best anatomy teaching method. Hence, exploring students' perceptions of cadaveric dissection will shed some light on how students experience and learn from dissection through their own reports rather than measuring their opinions concerning the importance of cadaveric dissection. In a more recent review, it was reported that there is no single best method to teach anatomy (Johnson et al., [<reflink idref="bib37" id="ref28">37</reflink>] ), and thus, to improve learning, it is necessary to evaluate the anatomy curriculum, mode and quality of teaching; and teaching facilities that are used for anatomy teaching (Papa and Vaccarezza, [<reflink idref="bib54" id="ref29">54</reflink>] ).</p> <p>Although this has been explored in several studies, it is also beneficial to evaluate students' perceptions of their anatomy knowledge and their confidence level when it comes to applying their knowledge during the clinical years (Prince et al., [<reflink idref="bib62" id="ref30">62</reflink>] ; Bergman et al., [<reflink idref="bib10" id="ref31">10</reflink>] ).Such evaluation provides input on intangible attributes concerning anatomy learning that reflect how the students are adapting to the anatomy curriculum in their institution. Effort should be also made to evaluate students' perceptions concerning the effectiveness of anatomy teaching, as there is decreasing number of qualified anatomy lecturers willing to teach anatomy (McCuskey et al., [<reflink idref="bib46" id="ref32">46</reflink>] ; Bay and Ling, [<reflink idref="bib7" id="ref33">7</reflink>] ). While it could be argued that the students lack credibility when it comes to rating their teachers, as their ratings mainly rely on their experience and observation, previous research has shown that students' ratings of instructional quality is a valid measure for teaching effectiveness and has positive correlations with other outcome variables, such as students' academic performance and motivation to learn (Christophel, [<reflink idref="bib19" id="ref34">19</reflink>] ; Kulik, [<reflink idref="bib40" id="ref35">40</reflink>] ; Muijs, [<reflink idref="bib50" id="ref36">50</reflink>] ).</p> <p>Measuring the aforementioned factors concerning the educational environment, however, requires a valid and reliable tool that specifically addresses elements of the anatomy education environment. Hence, a new inventory—termed the Anatomy Education Environment Measurement Inventory (AEEMI)—was developed by the authors using a Delphi method; the validity of this instrument was evaluated in the current study through four cross‐sectional interventions.</p> <p>In a broad sense, “validity” describes an instrument's ability to measure the attributes that it intends to measure (Streiner and Norman, [<reflink idref="bib72" id="ref37">72</reflink>] ). There are five sources of primary validity evidence outlined in the literature, which are the content, the response process, the internal structure, the relation to other variables, and the consequences of a measurement (Cook and Beckman, [<reflink idref="bib22" id="ref38">22</reflink>] ). In this study, the AEEMI's validity evidence was evaluated based on its content, response process, and internal structure.</p> <p>In general, the “content evidence of validity” determines how much the content of an inventory (i.e., statements or items asked in the questionnaire) represent the factors that the inventory intends to measure. For instance, an inventory that intends to measure stress levels should have items that address signs and symptoms of stress (e.g., “I have experienced frequent headaches for the past two weeks”). Content evidence can be presented as a detailed step‐by‐step approach that is carried out to ensure the representativeness of the items toward a factor (Haynes et al., [<reflink idref="bib33" id="ref39">33</reflink>] ), or it can be gauged by determining the content validity indices, as described by Polit et al. ([<reflink idref="bib59" id="ref40">59</reflink>] ).</p> <p>The “response process evidence of validity” measures the thought processes of users of the tested inventory as they respond to the tool. These are commonly evaluated in the form of clarity of instructions and language used in the tool, as well as the comprehensibility of instruction after training or an observation session (Cook and Beckman, [<reflink idref="bib22" id="ref41">22</reflink>] ). In contrast, the “internal structural evidence of validity” explores the reproducibility (i.e., internal consistency) of the users' responds across different time points, different raters, and different versions of the instrument; comparable responses across different demographic groups, such as race, gender, institution, and country (i.e., measurement invariance); and the dimensionality and patterns of item–factor relationships of an inventory (Rios and Wells, [<reflink idref="bib66" id="ref42">66</reflink>] ).</p> <p>All of these types of validity evidence further contribute to the construct validity of a measurement tool, (i.e., the tool's ability to really measure the factors it intends to measure). From that notion, this study was designed to provide the validity evidence for the AEEMI based on its content, response process, and internal structure. The best practice in developing and validating a measurement tool was adopted in this study, and this is described below.</p> <hd id="AN0124968752-2">Materials and Methods</hd> <hd id="AN0124968752-3">Study Design and Ethical Approval</hd> <p>This study was conducted in two phases: Phase 1 involves the development of the AEEMI, while Phase 2 entailed the validation process for the AEEMI. Ethical approval was obtained from the Human Research Ethic Committee, Universiti Sains Malaysia (USM).</p> <hd id="AN0124968752-4">Phase 1: Development of the Anatomy Education Environment Measurement Inventory Tool</hd> <p>The Delphi technique was employed to devise potential factors and items of the AEEMI based on experts' judgment. A factor is an unobserved (latent) variable, represented by a collection of observable variables (items) (Bartholomew et al., [<reflink idref="bib6" id="ref43">6</reflink>] ). Nine anatomists and five medical educationists were involved in this technique, which is an iterative process consisting of four stages (Linstone and Turoff, [<reflink idref="bib42" id="ref44">42</reflink>] ). During the first stage, the potential factors related to the anatomy education environment were explored through an open discussion and brainstorming session. To reach an understanding on how the group viewed anatomy education, each factor was defined in the second stage, and items related to each factor were devised through discussion. The results of the discussion were summarized in the third stage, and any disagreement was addressed at this time. The process was repeated until full consensus on the factors and items was achieved. The list of potential factors, definitions of the factors, and list of items underlying each factor were verified during the final evaluation in fourth stage. As a result of this exercise, 11 factors and 132 items were devised for the AEEMI (Supporting Information).</p> <hd id="AN0124968752-5">Phase 2: Validation of the Anatomy Education Environment Measurement Inventory Tool</hd> <hd id="AN0124968752-6">Content evidence of validity</hd> <p>The 11 factors and 132 items in the AEEMI were distributed to 10 anatomists from Malaysia, India, Australia, the United Kingdom, the United States, and Saudi Arabia for content evidence evaluation. Each factor was clearly defined and all items underlying it were listed accordingly. The experts were asked to rate their judgment on the degree of relevancy of each item to the measured factor (e.g., To what extent is item 41 in Supporting Information, “Anatomy questions are difficult,” relevant to factor 3 in Supporting Information,“Students' perceptions of anatomy assessment”).Their responses were measured using a five‐point Likert scale, which was defined as follows: 1 = the item is very irrelevant to the factor, 2 = the item is irrelevant to the factor, 3 = the item is acceptably relevant to the factor, 4 = the item is relevant to the factor, and Scale‐5 = the item is very relevant to the factor.</p> <p>To allow objective assessments of content evidence, the item‐level content validity index (I‐CVI) and scale‐level content validity index averaging (S‐CVI/Avg) method proposed by Polit et al. ([<reflink idref="bib59" id="ref45">59</reflink>] ) were modified from categorical into numerical indices. I‐CVI was gauged by calculating the mean relevancy score of each item (I‐CVI = sum of the relevancy score for each item divided by number of experts); the S‐CVI/Avg was determined by dividing the sum of I‐CVI by the total number of items (S‐CVI/Avg = [summation of all I‐CVI]/[number of items]). Since there were more than five experts involved in the evaluation, the lower limit of the acceptable value for both I‐CVI and S‐CVI/Avgwas 0.8 (Lynn, [<reflink idref="bib43" id="ref46">43</reflink>] ; Polit et al., [<reflink idref="bib59" id="ref47">59</reflink>] ). Items with an I‐CVI score of less than 0.8 were removed from the list, and the remaining items underwent response process validity evaluation. After the item removal process, the S‐CVI/Avg of the AEEMI was recalculated (using the scores of the remaining items) and compared with the S‐CVI/Avg of the 132‐item AEEMI version.</p> <hd id="AN0124968752-7">Response process evidence of validity</hd> <p>Based on the results of the content validity evaluation, 26 items were removed, and the remaining 106 items that had achieved an acceptable level of I‐CVI underwent response process validity evaluation. In this evaluation, the clarity of the language used to describe the items was evaluated by means of measuring thought processes of the AEEMI's users while they were answering the questions (Downing and Haladyna, [<reflink idref="bib27" id="ref48">27</reflink>] ; Cook and Beckman, [<reflink idref="bib22" id="ref49">22</reflink>] ). This evaluation was necessary in the Malaysian context, as English is not the first language of local students in this country.</p> <p>The evaluation was performed by distributing the 106 items of the AEEMI to 30 volunteer medical students from a public medical school. The sample size was determined by using the Roscoe rule of thumb for simple exploratory study—which is at least 30 samples (Roscoe, [<reflink idref="bib69" id="ref50">69</reflink>] ). The students were requested to rate their perceptions on the clarity of language used to describe each item using a five‐point Likert scale, as follows: 1 = the sentence is very vague, 2 = the sentence is vague, 3 = the sentence is acceptably clear, 4 = the sentence is clear, and 5 = the sentence is very clear.</p> <p>The item‐level clarity index (I‐CI) and scale‐level clarity index (S‐CI) were calculated using a similar method to that employed for the content validity indices. I‐CI was calculated by finding the mean of clarity scores for each item (I‐CI = sum of the clarity score for each item divided by the number of students), while, S‐CI/Avg was determined by dividing the sum of I‐CI by the total number of items (S‐CI/Avg = [summation of all I‐CI]/[number of items]). The lower limit of the acceptable value for all indices was 0.8 (Polit et al., [<reflink idref="bib59" id="ref51">59</reflink>] ).</p> <hd id="AN0124968752-8">Internal structure evidence of validity</hd> <p>The internal structure of the AEEMI was explored by evaluating the dimensionality (i.e., number of domains for the AEEMI) and item–factor relationships through factorial analyses; moreover, the internal consistency was determined through reliability analysis. The factorial analyses were performed in two stages, namely exploratory factor analysis (EFA) followed by confirmatory factor analysis (CFA). The initial possible domains of the AEEMI (i.e., factors that were to be measured by the validated version of the inventory) were derived through EFA; the results were then confirmed by CFA. Apart from determining the dimensionality, factorial analyses were performed to develop the best model‐fit for the AEEMI, a condition when the inventory had the optimal number of independent factors.</p> <p>Since all 106 items provided an I‐CI value of more than 0.8 in the response process validity evaluation, for EFA evaluation, these items were distributed to 325 volunteer first‐ and second‐year medical students at a public medical school in the 2012/2013 academic session. The sample size was determined according to the recommendation by Osborne and Costello ([<reflink idref="bib51" id="ref52">51</reflink>] ) for factorial analysis, which is that it should either be larger than five times the number of items or greater than 100. The students were requested to rate their perceptions of the anatomy education environment at their institution, as described by the 106 items that remained for response process evidence evaluation (e.g., Item‐7 in Supporting Information—Allotted teaching time for anatomy topics is sufficient) using a five‐point Likert scale, as follows: 1 = strongly disagree, 2 = disagree, 3 = not sure, agree, and 5 = strongly agree. Their responses were analyzed to determine the factor loading for each item and to explore the extractable factors using the Statistical Package for the Social Sciences (SPSS) software, version 22 (IBM Corp., Armonk, NY). The correlation matrix of the items was considered factorable when the Kaiser–Meyer–Olkin (KMO) value exceeded 0.5 and Bartlett's test was significant (DeCoster and Claypool, [<reflink idref="bib23" id="ref53">23</reflink>] ; Field, [<reflink idref="bib30" id="ref54">30</reflink>] ).The principal axis factoring (PAF) method was applied for the extraction of factors, from which factors with eigenvalues of over 1 were retained. Varimax rotation was applied to optimize the factor loading of each item on the extracted factors. Items with factor loadings of more than plus or minus 0.4 were selected for CFA (Stevens, [<reflink idref="bib71" id="ref55">71</reflink>] ).</p> <p>From the EFA results, 57 items that achieved a factor loading of plus or minus 0.4 were selected for CFA evaluation. These items were distributed to 483 volunteer first‐ and second‐year medical students at a public medical school in the 2013/2014 academic session. Likewise, the students were requested to rate their perceptions of the anatomy education environment at their institution, as described by the items, using the similar five‐point Likert‐scale to that employed in EFA. Their responses were analyzed to assess the dimensionality and model fit of AEEMI using the Analysis of Moment Structure (AMOS) software, version 19 (SPSS Inc., Chicago, IL), (Arbuckle, [<reflink idref="bib3" id="ref56">3</reflink>] ). From CFA, items that had modification indices of more than 15, standardized residual covariance of more than 2, and factor loadings of less than ±0.4 were removed until the best model fit was achieved. The best model fit was fulfilled when all of the fit indices had exceeded the minimum acceptable value, as summarized in Table [NaN] . The factors were considered independent from each other when correlation coefficients between the factors were less than 0.85 (Brown, [<reflink idref="bib15" id="ref57">15</reflink>] ).</p> <p>Goodness of Fit Indices That Were Used to Signify Model Fit</p> <p> <ephtml> &lt;table&gt;&lt;tr&gt;&lt;th align="left"&gt;Name of category&lt;/th&gt;&lt;th align="center"&gt;Name of index&lt;/th&gt;&lt;th align="center"&gt;Level of acceptance&lt;/th&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Absolute fit&lt;/td&gt;&lt;td align="left"&gt;Root mean square of error approximation (RMSEA)&lt;/td&gt;&lt;td align="left"&gt;Less than 0.08 (Browne and Cudeck, 16)&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td /&gt;&lt;td align="left"&gt;Goodness of fit index (GFI)&lt;/td&gt;&lt;td align="left"&gt;More than 0.9 (J&amp;#xf6;reskog and S&amp;#xf6;rbom, 38)&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Incremental fit&lt;/td&gt;&lt;td align="left"&gt;Comparative fit index (CFI)&lt;/td&gt;&lt;td align="left"&gt;More than 0.9 (Bentler, 8)&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td /&gt;&lt;td align="left"&gt;Tucker&amp;#x2013;Lewis index (TLI)&lt;/td&gt;&lt;td align="left"&gt;More than 0.9 (Bentler and Bonett, 9)&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td /&gt;&lt;td align="left"&gt;Normed fit index (NFI)&lt;/td&gt;&lt;td align="left"&gt;More than 0.9 (Bollen, 14)&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Parsimonious fit&lt;/td&gt;&lt;td align="left"&gt;Chi square/degree of freedom (&amp;#x3c7;&lt;sup&gt;2&lt;/sup&gt;/df)&lt;/td&gt;&lt;td align="left"&gt;Less than 5 (Marsh and Hocevar, 45)&lt;/td&gt;&lt;/tr&gt;&lt;/table&gt; </ephtml> </p> <p>1 Absolute fit: Measures overall goodness of fit for both the structural and measurement models collectively. This type of measure does not make any comparison to a specified null model (incremental fit measure) or adjust for the number of parameters in the estimated model (parsimonious fit measure);</p> <ulist> <item>2 Incremental fit: Measures goodness of fit that compares the current model to a specified “null” (independence) model to determine the degree of improvement over the null model;</item> <item>3 Parsimonious fit: Measures goodness of fit representing the degree of model fit per estimated coefficient. This measure attempts to correct for any “overfitting” of the model and evaluates the parsimony of the model compared to the goodness of fit.</item> </ulist> <p>The internal consistency of the AEEMI was determined by exploring the relationships among items that represent a similar domain. The CFA data were used to calculate the composite reliability coefficients proposed by Raykov ([<reflink idref="bib65" id="ref58">65</reflink>] ); this was done using the semTools package in the R software (Pornprasertmanit et al., [<reflink idref="bib60" id="ref59">60</reflink>] ). Values of composite reliability coefficients of 0.7–0.8 were considered satisfactory (Bland and Altman, [<reflink idref="bib12" id="ref60">12</reflink>] ), although this guideline is meant for the Cronbach's alpha coefficient. The workflow of the development and validation of AEEMI is summarized in Figure [NaN] .</p> <hd id="AN0124968752-9">Results</hd> <hd id="AN0124968752-10">Content Evidence of Validity</hd> <p>The analysis of the 132‐item version of AEEMI revealed that S‐CVI/Avg achieved 0.8 for 8 out of 11 factors of the AEEMI. From 132 items, 26 failed to achieve an I‐CVI value of 0.8; hence, they were not included for subsequent response process evidence of validity evaluation. The S‐CVI/Avg for all 11 factors and the total S‐CVI/Avg of the AEEMI improved after the item removal process as the indices exceeded 0.8. The results are summarized in Table [NaN] .</p> <p>The Content and Response Process Validity Evidence of the Anatomy Education Environment Measurement Inventory (AEEMI)</p> <p> <ephtml> &lt;table&gt;&lt;tr&gt;&lt;th align="left" /&gt;&lt;th align="center"&gt;Content validity&lt;/th&gt;&lt;th align="center"&gt;Response process validity&lt;/th&gt;&lt;/tr&gt;&lt;tr&gt;&lt;th&gt;Factors of the AEEMI&lt;/th&gt;&lt;th align="center"&gt;S&amp;#x2010;CVI/Avg (132 items)&lt;/th&gt;&lt;th align="center"&gt;S&amp;#x2010;CVI/Avg (106 items)&lt;/th&gt;&lt;th align="center"&gt;S&amp;#x2010;CI/Avg (106 items)&lt;/th&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Factor 1: Students' perceptions of anatomy teaching methodologies&lt;/td&gt;&lt;td align="char" char="."&gt;0.79&lt;/td&gt;&lt;td align="char" char="."&gt;0.86&lt;/td&gt;&lt;td align="char" char="."&gt;0.97&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Factor 2: Students' perceptions of learning anatomy&lt;/td&gt;&lt;td align="char" char="."&gt;0.86&lt;/td&gt;&lt;td align="char" char="."&gt;0.89&lt;/td&gt;&lt;td align="char" char="."&gt;0.99&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Factor 3: Students' perceptions of anatomy assessments&lt;/td&gt;&lt;td align="char" char="."&gt;0.82&lt;/td&gt;&lt;td align="char" char="."&gt;0.94&lt;/td&gt;&lt;td align="char" char="."&gt;0.96&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Factor 4: Students' perceptions on anatomy content knowledge&lt;/td&gt;&lt;td align="char" char="."&gt;0.80&lt;/td&gt;&lt;td align="char" char="."&gt;0.88&lt;/td&gt;&lt;td align="char" char="."&gt;0.98&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Factor 5: Students' perceptions of anatomy teachers&lt;/td&gt;&lt;td align="char" char="."&gt;0.92&lt;/td&gt;&lt;td align="char" char="."&gt;0.96&lt;/td&gt;&lt;td align="char" char="."&gt;0.98&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Factor 6: Students' perceptions of the anatomy learning atmosphere&lt;/td&gt;&lt;td align="char" char="."&gt;0.77&lt;/td&gt;&lt;td align="char" char="."&gt;0.86&lt;/td&gt;&lt;td align="char" char="."&gt;0.98&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Factor 7: Students' perceptions of teaching and learning tools&lt;/td&gt;&lt;td align="char" char="."&gt;0.85&lt;/td&gt;&lt;td align="char" char="."&gt;0.92&lt;/td&gt;&lt;td align="char" char="."&gt;0.96&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Factor 8: Students' self&amp;#x2010;perceptions concerning interest in anatomy&lt;/td&gt;&lt;td align="char" char="."&gt;0.89&lt;/td&gt;&lt;td align="char" char="."&gt;0.98&lt;/td&gt;&lt;td align="char" char="."&gt;0.99&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Factor 9: Students' self&amp;#x2010;perceptions concerning anatomy comprehension&lt;/td&gt;&lt;td align="char" char="."&gt;0.78&lt;/td&gt;&lt;td align="char" char="."&gt;0.86&lt;/td&gt;&lt;td align="char" char="."&gt;0.98&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Factor 10: Students' self&amp;#x2010;perceptions concerning anatomy integration and application&lt;/td&gt;&lt;td align="char" char="."&gt;0.88&lt;/td&gt;&lt;td align="char" char="."&gt;0.95&lt;/td&gt;&lt;td align="char" char="."&gt;1.00&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Factor 11: Students' self&amp;#x2010;perceptions concerning anatomy learning and revision&lt;/td&gt;&lt;td align="char" char="."&gt;0.79&lt;/td&gt;&lt;td align="char" char="."&gt;0.82&lt;/td&gt;&lt;td align="char" char="."&gt;0.97&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Overall&lt;/td&gt;&lt;td align="char" char="."&gt;0.83&lt;/td&gt;&lt;td align="char" char="."&gt;0.90&lt;/td&gt;&lt;td align="char" char="."&gt;0.98&lt;/td&gt;&lt;/tr&gt;&lt;/table&gt; </ephtml> </p> <p>4 The AEEMI factors generated by the Delphi technique; S‐CVI/Avg, scale‐level content validity index/averages; S‐CI/Avg, scale‐level clarity index/averages.</p> <hd id="AN0124968752-11">Response Process Evidence of Validity</hd> <p>It was revealed that the S‐CI of the eleven factors and overall S‐CI/Avg of the AEEMI exceeded 0.8. Likewise, all 106 items achieved an I‐CI of more than 0.8; hence, these items were retained for further internal structure evaluation.</p> <hd id="AN0124968752-12">Internal Structure Evidence of Validity</hd> <hd id="AN0124968752-13">Exploratory factor analysis</hd> <p>It was revealed from the EFA that the items' correlation matrix was factorable, with a KMO value of 0.695 and a significant Bartlett's test of sphericity [Bartlett's χ<sups>2</sups> (2016) = 4,350.251, P &lt; 0.001]. Using the varimax rotation in PAF, the factor loading of each item on the extracted components for interpretability was optimized. Items with factor loadings of less than plus or minus 0.4 were removed and the remaining 57 items were found to load on eight domains were selected for further confirmatory factor analysis.</p> <hd id="AN0124968752-14">Confirmatory factor analysis</hd> <p>It was conformed from the CFA that the AEEMI is a multidimensional model, but the eight‐domain model of the AEEMI as suggested by EFA result, failed to achieve acceptable values of the goodness‐of‐fit indices, suggesting poor model fit. Removal of items was performed iteratively based on the items' modification indices, standardized residual covariance, and factor loadings to improve the model fit. The model fit was achieved only after the removal of 31 items; the remaining 25 items were found to load into six domains with standardized correlation coefficients between domains of less than 0.85. The results for the AEEMI's dimensionality are summarized in Table [NaN] .</p> <p>The Results of Confirmatory Factor Analysis of the Anatomy Education Environment Measurement Inventory</p> <p> <ephtml> &lt;table&gt;&lt;tr&gt;&lt;th align="left" /&gt;&lt;th align="center" /&gt;&lt;th align="center" /&gt;&lt;th align="center"&gt;Goodness of fit indices&lt;/th&gt;&lt;/tr&gt;&lt;tr&gt;&lt;th&gt;Variable&lt;/th&gt;&lt;th&gt;&amp;#x3c7;&lt;sup&gt;2&lt;/sup&gt; statistic (df)&lt;/th&gt;&lt;th&gt;P&amp;#x2010;value&lt;/th&gt;&lt;th align="center"&gt;&amp;#x3c7;&lt;sup&gt;2&lt;/sup&gt;/df&lt;/th&gt;&lt;th align="center"&gt;RMSEA&lt;/th&gt;&lt;th align="center"&gt;GFI&lt;/th&gt;&lt;th align="center"&gt;CFI&lt;/th&gt;&lt;th align="center"&gt;NFI&lt;/th&gt;&lt;th align="center"&gt;TLI&lt;/th&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;One&amp;#x2010;domain model&lt;/td&gt;&lt;td align="center"&gt;4,187.78 (1,377)&lt;/td&gt;&lt;td align="char" char="&lt;"&gt;&lt;0.001&lt;/td&gt;&lt;td align="char" char="."&gt;3.041&lt;/td&gt;&lt;td align="char" char="."&gt;0.082&lt;/td&gt;&lt;td align="char" char="."&gt;0.613&lt;/td&gt;&lt;td align="char" char="."&gt;0.517&lt;/td&gt;&lt;td align="char" char="."&gt;0.423&lt;/td&gt;&lt;td align="char" char="."&gt;0.498&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Eight&amp;#x2010;domain model&lt;/td&gt;&lt;td align="center"&gt;2,832.89 (1,341)&lt;/td&gt;&lt;td align="char" char="&lt;"&gt;&lt;0.001&lt;/td&gt;&lt;td align="char" char="."&gt;2.113&lt;/td&gt;&lt;td align="char" char="."&gt;0.060&lt;/td&gt;&lt;td align="char" char="."&gt;0.743&lt;/td&gt;&lt;td align="char" char="."&gt;0.744&lt;/td&gt;&lt;td align="char" char="."&gt;0.609&lt;/td&gt;&lt;td align="char" char="."&gt;0.727&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Six&amp;#x2010;domain model&lt;/td&gt;&lt;td align="char" char="."&gt;415.67 (255)&lt;/td&gt;&lt;td align="char" char="&lt;"&gt;&lt;0.001&lt;/td&gt;&lt;td align="char" char="."&gt;1.63&lt;/td&gt;&lt;td align="char" char="."&gt;0.045&lt;/td&gt;&lt;td align="char" char="."&gt;0.905&lt;/td&gt;&lt;td align="char" char="."&gt;0.937&lt;/td&gt;&lt;td align="char" char="."&gt;0.854&lt;/td&gt;&lt;td align="char" char="."&gt;0.926&lt;/td&gt;&lt;/tr&gt;&lt;/table&gt; </ephtml> </p> <p>5 Based on the proposed construct using exploratory factor analysis—56 items; bBased on the final model—25 items; χ2/df, Chi square/degree of freedom; RMSEA, root mean square of error approximation; GFI, goodness of fit index; CFI, comparative fit index; NFI, normed fit index; TLI, Tucker–Lewis index.</p> <hd id="AN0124968752-15">Internal consistency</hd> <p>The composite reliability estimates of the AEEMI domains were in the range of 0.604–0.868, suggesting acceptable high internal consistency. Hence, the final validated version of the AEEMI was composed of six domains with 25 underlying items. Each domain was named based on the common description interpreted from the items. The I‐CVI, factor loadings, and Raykov rho reliability estimates for the final 25 items of AEEMI are presented in Table [NaN] .</p> <p>The I‐CVI, Factor Loadings, and Reliability of the Six Domains of the Anatomy Education Environment Measurement Inventory (Final Model)</p> <p> <ephtml> &lt;table&gt;&lt;tr&gt;&lt;th align="left"&gt;Domains&lt;/th&gt;&lt;th align="center"&gt;Items&lt;/th&gt;&lt;th align="center"&gt;I&amp;#x2010;CVI&lt;/th&gt;&lt;th align="center"&gt;&amp;#x3bb; EFA&lt;/th&gt;&lt;th align="center"&gt;&amp;#x3bb; CFA&lt;/th&gt;&lt;th align="center"&gt;Raykov's rho&lt;/th&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Students' perceptions of anatomy teachers&lt;/td&gt;&lt;td align="left"&gt;Teachers are knowledgeable&lt;/td&gt;&lt;td align="char" char="."&gt;1.00&lt;/td&gt;&lt;td align="char" char="."&gt;0.53&lt;/td&gt;&lt;td align="char" char="."&gt;0.65&lt;/td&gt;&lt;td align="char" char="."&gt;0.876&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Anatomy teachers are available to help students&lt;/td&gt;&lt;td align="char" char="."&gt;1.00&lt;/td&gt;&lt;td align="char" char="."&gt;0.67&lt;/td&gt;&lt;td align="char" char="."&gt;0.60&lt;/td&gt;&lt;td /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td /&gt;&lt;td align="left"&gt;Teachers are friendly&lt;/td&gt;&lt;td align="char" char="."&gt;1.00&lt;/td&gt;&lt;td align="char" char="."&gt;0.51&lt;/td&gt;&lt;td align="char" char="."&gt;0.72&lt;/td&gt;&lt;td /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td /&gt;&lt;td align="left"&gt;Teachers are enthusiastic to teach&lt;/td&gt;&lt;td align="char" char="."&gt;1.00&lt;/td&gt;&lt;td align="char" char="."&gt;0.76&lt;/td&gt;&lt;td align="char" char="."&gt;0.63&lt;/td&gt;&lt;td /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td /&gt;&lt;td align="left"&gt;Teachers are well prepared&lt;/td&gt;&lt;td align="char" char="."&gt;1.00&lt;/td&gt;&lt;td align="char" char="."&gt;0.68&lt;/td&gt;&lt;td align="char" char="."&gt;0.76&lt;/td&gt;&lt;td /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td /&gt;&lt;td align="left"&gt;Teachers are good role models for learning anatomy&lt;/td&gt;&lt;td align="char" char="."&gt;1.00&lt;/td&gt;&lt;td align="char" char="."&gt;0.56&lt;/td&gt;&lt;td align="char" char="."&gt;0.72&lt;/td&gt;&lt;td /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td /&gt;&lt;td align="left"&gt;Teachers are approachable&lt;/td&gt;&lt;td align="char" char="."&gt;1.00&lt;/td&gt;&lt;td align="char" char="."&gt;0.70&lt;/td&gt;&lt;td align="char" char="."&gt;0.75&lt;/td&gt;&lt;td /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Students' perceptions of the importance of anatomy knowledge&lt;/td&gt;&lt;td align="left"&gt;My anatomy knowledge helps me to understand other medical subjects&lt;/td&gt;&lt;td align="char" char="."&gt;1.00&lt;/td&gt;&lt;td align="char" char="."&gt;0.64&lt;/td&gt;&lt;td align="char" char="."&gt;0.59&lt;/td&gt;&lt;td align="char" char="."&gt;0.846&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td /&gt;&lt;td align="left"&gt;The anatomy topics prepare me for clinical years&lt;/td&gt;&lt;td align="char" char="."&gt;1.00&lt;/td&gt;&lt;td align="char" char="."&gt;0.57&lt;/td&gt;&lt;td align="char" char="."&gt;0.71&lt;/td&gt;&lt;td /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td /&gt;&lt;td align="left"&gt;The Anatomy subject gives me feeling of becoming a doctor&lt;/td&gt;&lt;td align="char" char="."&gt;1.00&lt;/td&gt;&lt;td align="char" char="."&gt;0.45&lt;/td&gt;&lt;td align="char" char="."&gt;0.62&lt;/td&gt;&lt;td /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td /&gt;&lt;td align="left"&gt;I can apply my anatomical knowledge in clinical years&lt;/td&gt;&lt;td align="char" char="."&gt;1.00&lt;/td&gt;&lt;td align="char" char="."&gt;0.66&lt;/td&gt;&lt;td align="char" char="."&gt;0.70&lt;/td&gt;&lt;td /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td /&gt;&lt;td align="left"&gt;The anatomy topics are relevant to my future profession&lt;/td&gt;&lt;td align="char" char="."&gt;0.86&lt;/td&gt;&lt;td align="char" char="."&gt;0.61&lt;/td&gt;&lt;td align="char" char="."&gt;0.77&lt;/td&gt;&lt;td /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td /&gt;&lt;td align="left"&gt;Relevant anatomy topics are reemphasized in clinical years&lt;/td&gt;&lt;td align="char" char="."&gt;1.00&lt;/td&gt;&lt;td align="char" char="."&gt;0.48&lt;/td&gt;&lt;td align="char" char="."&gt;0.49&lt;/td&gt;&lt;td /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td /&gt;&lt;td align="left"&gt;Learning anatomy prepared me to be a good doctor&lt;/td&gt;&lt;td align="char" char="."&gt;0.86&lt;/td&gt;&lt;td align="char" char="."&gt;0.70&lt;/td&gt;&lt;td align="char" char="."&gt;0.69&lt;/td&gt;&lt;td /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Students' perception of anatomy subject&lt;/td&gt;&lt;td align="left"&gt;Learning anatomy is fun&lt;/td&gt;&lt;td align="char" char="."&gt;1.00&lt;/td&gt;&lt;td align="char" char="."&gt;0.58&lt;/td&gt;&lt;td align="char" char="."&gt;0.79&lt;/td&gt;&lt;td align="char" char="."&gt;0.761&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;I am confident that I can answer anatomy questions well&lt;/td&gt;&lt;td align="char" char="."&gt;0.86&lt;/td&gt;&lt;td align="char" char="."&gt;0.74&lt;/td&gt;&lt;td align="char" char="."&gt;0.47&lt;/td&gt;&lt;td /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td /&gt;&lt;td align="left"&gt;Anatomy is an interesting subject&lt;/td&gt;&lt;td align="char" char="."&gt;1.00&lt;/td&gt;&lt;td align="char" char="."&gt;0.52&lt;/td&gt;&lt;td align="char" char="."&gt;0.87&lt;/td&gt;&lt;td /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Students' perceptions of anatomy learning resources&lt;/td&gt;&lt;td align="left"&gt;Practical sessions are well organized&lt;/td&gt;&lt;td align="char" char="."&gt;0.86&lt;/td&gt;&lt;td align="char" char="."&gt;0.40&lt;/td&gt;&lt;td align="char" char="."&gt;0.67&lt;/td&gt;&lt;td align="char" char="."&gt;0.604&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;The prosected specimens are accessible&lt;/td&gt;&lt;td align="char" char="."&gt;0.86&lt;/td&gt;&lt;td align="char" char="."&gt;0.65&lt;/td&gt;&lt;td align="char" char="."&gt;0.42&lt;/td&gt;&lt;td /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td /&gt;&lt;td align="left"&gt;Learning facilities are well maintained&lt;/td&gt;&lt;td align="char" char="."&gt;1.00&lt;/td&gt;&lt;td align="char" char="."&gt;0.57&lt;/td&gt;&lt;td align="char" char="."&gt;0.63&lt;/td&gt;&lt;td /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Students' perception of their efforts to learn anatomy&lt;/td&gt;&lt;td align="left"&gt;I utilize the anatomy museum to learn anatomy&lt;/td&gt;&lt;td align="char" char="."&gt;1.00&lt;/td&gt;&lt;td align="char" char="."&gt;0.56&lt;/td&gt;&lt;td align="char" char="."&gt;0.48&lt;/td&gt;&lt;td align="char" char="."&gt;0.669&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td /&gt;&lt;td align="left"&gt;I use anatomy models/specimens to learn anatomy&lt;/td&gt;&lt;td align="char" char="."&gt;1.00&lt;/td&gt;&lt;td align="char" char="."&gt;0.60&lt;/td&gt;&lt;td align="char" char="."&gt;0.66&lt;/td&gt;&lt;td /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td /&gt;&lt;td align="left"&gt;Anatomy examinations help me to identify my weaknesses about anatomy knowledge&lt;/td&gt;&lt;td align="char" char="."&gt;1.00&lt;/td&gt;&lt;td align="char" char="."&gt;0.41&lt;/td&gt;&lt;td align="char" char="."&gt;0.70&lt;/td&gt;&lt;td /&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;Students' perceptions of the quality of histology learning facilities&lt;/td&gt;&lt;td align="left"&gt;The quality of microscopes provided to study histology slides is poor&lt;/td&gt;&lt;td align="char" char="."&gt;0.86&lt;/td&gt;&lt;td align="char" char="."&gt;0.75&lt;/td&gt;&lt;td align="char" char="."&gt;0.88&lt;/td&gt;&lt;td align="char" char="."&gt;0.711&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td /&gt;&lt;td align="left"&gt;Histology slides are of poor quality&lt;/td&gt;&lt;td align="char" char="."&gt;1.00&lt;/td&gt;&lt;td align="char" char="."&gt;0.74&lt;/td&gt;&lt;td align="char" char="."&gt;0.58&lt;/td&gt;&lt;td /&gt;&lt;/tr&gt;&lt;/table&gt; </ephtml> </p> <ulist> <item>6 aConstructs were determined based on expert judgments on content; bTwenty‐five final items of the anatomy education environment measurement inventory (AEEMI); The full list of 132 AEEMI items (on development) is provided in the Supporting Information; cRaykov's rho coefficient as a reliability estimate; dNegative items that were reverse scored;</item> <item>7 λ, factor loading; EFA, exploratory factor analysis; CFA, confirmatory factor analysis; I‐CVI, item‐level content validity index.</item> </ulist> <hd id="AN0124968752-16">Discussion</hd> <p>It was evident from this study that the final six‐factor and 25‐item version of AEEMI is construct valid, as this inventory was demonstrated to display good content, response process, and internal structure validity evidence. Although the AEEMI items were constructed using a solid framework of the Delphi technique, the original 132‐item version of the AEEMI suffered extensive item removal. The statistical validation approach, mainly using the EFA, CFA, and composite reliability enabled the exclusion of large number of items that were redundant and did not clearly represent any factors; hence, they allowed for refinement of the initially proposed AEEMI framework. In other words, the final version of the AEEMI comprises clearly defined, nonredundant factors with small pools of items.</p> <p>The six factors of AEEMI, namely students' perceptions of anatomy teachers (seven items), students' perceptions of the importance of anatomy knowledge (seven items), students' perception of anatomy subject (three items), students' perceptions of anatomy learning resources (three items); students' perception of their efforts to learn anatomy (three items), and students' perceptions of the quality of histology learning facilities (two items), are aligned with issues of anatomy education being addressed in the literature. For instance, the first factor—students' perceptions of anatomy teachers and—is aligned with the current issue of the inadequate number of qualified anatomy lecturers who are willing to teach anatomy (Pabst and Rothkötter, [<reflink idref="bib52" id="ref61">52</reflink>] ; McCuskey et al., [<reflink idref="bib46" id="ref62">46</reflink>] ; Raftery, [<reflink idref="bib63" id="ref63">63</reflink>] ; Bay and Ling, [<reflink idref="bib7" id="ref64">7</reflink>] ). This factor is represented by seven items that measure students' perception of their teachers' content knowledge and teaching behaviors rather than the teachers' seniority and popularity. Similarly, the items for the second and third factors(i.e., students' perceptions of the importance of anatomy knowledge and students' intrinsic interest in learning anatomy, respectively) are congruent with previous research reporting on the importance of anatomy knowledge (Tibrewal, [<reflink idref="bib73" id="ref65">73</reflink>] ; Dickson et al., [<reflink idref="bib26" id="ref66">26</reflink>] ; Böckers et al., [<reflink idref="bib13" id="ref67">13</reflink>] ), which has been characterized as declining among medical students and graduates (McKeown et al., [<reflink idref="bib47" id="ref68">47</reflink>] ; Prince et al., [<reflink idref="bib61" id="ref69">61</reflink>] ; Spielmann and Oliver, [<reflink idref="bib70" id="ref70">70</reflink>] ). As for the other three factors, they contain items that share similar characteristic features that describe the quality and accessibility of teaching tools, learning resources, and assessment in anatomy education. These factors correspond with educators' and students' growing interest in using different types of anatomy teaching modalities and resources (Pandey and Zimitat, [<reflink idref="bib53" id="ref71">53</reflink>] ; Turney, [<reflink idref="bib75" id="ref72">75</reflink>] ; Ganguly, [<reflink idref="bib32" id="ref73">32</reflink>] ; Johnson et al., [<reflink idref="bib37" id="ref74">37</reflink>] ). The constructive alignment between these AEEMI factors and the global issues of anatomy education indicates that the content of AEEMI covers relevant constructs of the anatomy education environment, and thus enhances its validity credential.</p> <p>The first validity evaluation of AEEMI, namely content evidence, began as early as in the development phase, when factors and items of AEEMI were devised using the Delphi technique, an iterative robust method to achieve consensus among experts on specific real issues (Hsu and Sandford, [<reflink idref="bib35" id="ref75">35</reflink>] ). During this stage, precise definitions of expected factors were constructed by the experts, allowing clear distinctions between factors to be made explicit; this guided the experts on the item‐construction process (Haynes et al., [<reflink idref="bib33" id="ref76">33</reflink>] ). Furthermore, the use of a large number of items in this study was aligned with recommendations from several studies, including the following: the number of items should be adequate enough to cover the intended outcomes, items should undergo proper selection and weighting of relevant attributes to be assessed, and a group of items should collectively indicate the operational definition of a factor (Polit and Beck, [<reflink idref="bib58" id="ref77">58</reflink>] ; Polit et al., [<reflink idref="bib59" id="ref78">59</reflink>] ; Streiner and Norman, [<reflink idref="bib72" id="ref79">72</reflink>] ).</p> <p>Objective measures of content evidence were also evaluated in this study through the calculation of the content validity indices, which reflect the degree of relevancy of each item to the factors perceived by experts from different countries (Polit et al., [<reflink idref="bib59" id="ref80">59</reflink>] ). Therefore, a clear inference of items could be drawn from any data measured using the AEEMI (Haynes et al., [<reflink idref="bib33" id="ref81">33</reflink>] ). The content validity indices of the 106‐item version of AEEMI were found to be higher than those of the original 132‐item version, indicating that some items in the original list of the AEEMI may not be relevant across different settings and institutions. These results reflected the variation in the anatomy education environment across different countries and institutions, and the remaining items perhaps indicate similarities in the global anatomy community (Collins et al., [<reflink idref="bib21" id="ref82">21</reflink>] ; Heylings, [<reflink idref="bib34" id="ref83">34</reflink>] ; Kagan, [<reflink idref="bib39" id="ref84">39</reflink>] ; Elizondo‐Omaña et al., [<reflink idref="bib28" id="ref85">28</reflink>] ).</p> <p>The AEEMI was demonstrated to have good response process validity, as all 106 AEEMI items were found to have high clarity indices. By measuring the clarity of language used in the inventory, any conflicting perceptions between developers and users concerning the items' structure were eliminated (DeVon et al., [<reflink idref="bib25" id="ref86">25</reflink>] ). Although it could be argued that response process evaluation in this study resembled face validity in terms of the “appearance of validity” (i.e., apart from being valid, the inventory should appears valid) (Mosier, [<reflink idref="bib49" id="ref87">49</reflink>] ), which is not regarded as validity evidence (Downing and Haladyna, [<reflink idref="bib27" id="ref88">27</reflink>] ; Cook and Beckman, [<reflink idref="bib22" id="ref89">22</reflink>] ), the appearance of validity of the AEEMI would be able to prevent erroneous interpretation of the items, as ambiguous elements were excluded from the evaluation.</p> <p>The third evidence of validity was the internal structure of AEEMI, which was evaluated through EFA, CFA, and composite reliability analysis. Through EFA and CFA, six factors of the anatomy educational environment were identified, indicating that the AEEMI is a multidimensional inventory. Since this inventory is a multifactorial scale, the composite reliability estimate is a better representation of the reliability measure than Cronbach's alpha, as it corrects the negative and positive biases (Raykov, [<reflink idref="bib64" id="ref90">64</reflink>] ; MacDougall, [<reflink idref="bib44" id="ref91">44</reflink>] ). The acceptable‐to‐high Raykov reliability estimate of the AEEMI indicated good internal consistency of the factors, further supporting the internal structure of the AEEMI. However, AEEMI was noted to have some drawbacks; and for that reason, the use of this inventory is currently limited to measuring the anatomy education environment in USM.</p> <p>Ever since its establishment, USM has adopted the integrated organ system–based approach (Lim, [<reflink idref="bib41" id="ref92">41</reflink>] ). Anatomy education at USM consists of gross anatomy, histology, embryology, and neuroanatomy, which are taught in first three of five years of the medical degree program. Different teaching modalities are applied, but lectures remain the main method of conveying anatomy information to students, representing 104 total teaching hours per year. In view of the limited numbers of cadavers and the lack of success of the body donation program at USM, cadaveric dissection is used to teach postgraduate students only. However, undergraduate students have the opportunity to learn anatomy using cadaveric prosected and plastinated specimens, as well as plastic anatomy models, during practical sessions. These specimens are also made available to students in the anatomy museum for self‐revision. In addition to lectures, anatomy inputs are also integrated and reinforced in PBL sessions, and students can easily assess the suggested learning materials provided through the university's e‐learning portal. As for assessment, anatomy knowledge is tested through integrated multiple choice questions, short essay questions, scenario‐based questions, and objective structured practical examination (OSPE).</p> <hd id="AN0124968752-17">Limitations</hd> <p>The major limitation lies in the coverage of AEEMI items, as some of the items that were removed may represent important components pertinent to anatomy education. For example, the initial version of the inventory outlined 15 items related to anatomy assessment—one of the major components in the education environment—and three items related to the use of cadaveric specimens, but only one item of each component remained in the final version of the AEEMI. The reason for this result could be related to the nature of this study, as it was conducted in a single center (i.e., USM), as well as the homogeneity of the study participants (i.e., preclinical‐year medical students). Therefore, the coverage of items may be confined to the USM anatomy education environment.</p> <p>In view of the integrated nature of questions used during anatomy assessment, it was postulated that the study participants involved in the EFA and CFA in this study may have had difficulty responding to some of the items used in the evaluation; thus resulted in the removal of these items. A number of relevant items may have been falsely removed due to this limitation. To address this issue, a revised version of the inventory could be proposed by revisiting the items and revalidating the AEEMI. Cross‐validation studies utilizing the full 106‐item version of the AEEMI to other cohorts of medical students including clinical‐year students, in other universities, could be conducted to improve its psychometric credentials.</p> <p>Another important validity evidence that was not investigated in this study is the “relationship with other variables.” The investigation of this validity evidence could be carried out by identifying observable factors related to the inventory at hand or correlating the inventory with other inventories measuring the same factors (Cook and Beckman, [<reflink idref="bib22" id="ref93">22</reflink>] ). Bringing this point into the current context, the former could possibly be done, as one of the AEEMI's factors—students' perceptions of the importance of anatomy knowledge—are aligned with two out of the five themes that emerged from a qualitative phenomenological study by Bergman et al. ([<reflink idref="bib11" id="ref94">11</reflink>] ).These researchers attempted to explore medical students' perceptions of undergraduate anatomy teaching in a Problem Based Learning (PBL) curriculum through a series of focus group discussions. The two related themes are the relevance of anatomical knowledge, and the use of anatomical knowledge in clinical practice (Bergman et al., [<reflink idref="bib11" id="ref95">11</reflink>] ). However, correlating the AEEMI with other inventories of measuring the same factors is not possible due to the absence of locally validated inventories measuring the anatomy education environment. Studies focusing on providing evidence by relating the AEEMI scores with factors associated with the environment are thus recommended.</p> <hd id="AN0124968752-18">Conclusions</hd> <p>This study provided evidence to support the validity of the AEEMI as a tool to measure the anatomy education environment for medical students at the USM medical school. Although the inventory may be valid for medical students at other universities, as it could be assumed that the environment is similar, the results should be interpreted with cautions until the items have been verified by conducting cross‐validation studies in the other Malaysian medical schools. On a more global scale, the inventory could be validated in medical schools in other English‐speaking countries, since the AEEMI is an English inventory. Perhaps, it is beneficial to add more items that could represent global anatomy education environment—as to increase its generalizability—by involving more experts from other countries. It is important for anatomy educators to work together in the global context to further strengthen the psychometric credentials of the AEEMI. If this collaborative work could be materialized, the AEEMI could appear as a standard, universal tool to measure the anatomy education environment in medical schools.</p> <hd id="AN0124968752-19">ACKNOWLEDGMENTS</hd> <p>The authors would like to thank the Universiti Sains Malaysia for allowing us to conduct this study in their institutions. Last but not least, our greatest appreciation to the anatomy experts and pre‐clinical years medical students who had participated in this study.</p> <hd id="AN0124968752-20">Notes on Contributors</hd> <p>SITI NURMA HANIM HADIE, M.D., M.Sc. (Clin. Anat.), is a medical lecturer in the Department of Anatomy at the School of Medical Sciences, Health Campus, Universiti Sains Malaysia, Kelantan, Malaysia. She teaches gross anatomy, histology and embryology to undergraduate medical students.</p> <p>ASMA' HASSAN, M.B.B.S., M. Med.Sc. (Anat.), Ph.D., is a professor in the Faculty of Medicine, Medical Campus, Universiti Sultan Zainal Abidin (UniSZA), Terengganu, Malaysia. She teaches gross anatomy, histology and embryology to undergraduate medical students.</p> <p>ZUL IZHAR MOHD ISMAIL, M.B.B.S., M.Phil, is an associate professor and the Phase 1 Chairman of Medical Degree Program in the School of Medical Sciences, Health Campus, Universiti Sains Malaysia, Kelantan, Malaysia. He teaches gross anatomy, histology and embryology to undergraduate medical students.</p> <p>MOHD ASNIZAM ASARI, M.B.B.S., M.Sc. (Clin. Anat.), is an associate professor and Head of the Department of Anatomy in the School of Medical Sciences, Health Campus, Universiti Sains Malaysia, Kelantan, Malaysia. His research interests include anatomy education, neurotoxicology and natural products. He teaches gross anatomy, histology and embryology to undergraduate medical students.</p> <p>AAIJAZ AHMED KHAN, M.B.B.S., M.S. (Anat.), was a senior medical lecturer in the Department of Anatomy, School of Medical Sciences, Health Campus, Universiti Sains Malaysia, Kelantan. Malaysia. He taught gross anatomy, histology and embryology to undergraduate medical students.</p> <p>FAZLINA KASIM, M.B.B.S., M.Sc. (Clin. Anat.), is a medical lecturer in the Department of Anatomy, at the School of Medical Sciences, Health Campus, Universiti Sains Malaysia, Kota Bharu, Kelantan, Malaysia. Her research interests include anatomy education and histology.</p> <p>NURUL AIMAN MOHD YUSOF, MD, M.Sc. (Clin. Anat.), is a medical lecturer in the Department of Anatomy, at the School of Medical Sciences, Health Campus, Universiti Sains Malaysia, Kelantan, Malaysia. She teaches gross anatomy, histology and embryology to undergraduate medical students.</p> <p>HUSNAIDA ABDUL MANAN@SULONG, M.D., M.Sc. (Clin. Anat.), is a medical lecturer in the Department of Anatomy, at the School of Medical Sciences, Health Campus, Universiti Sains Malaysia, Kelantan, Malaysia. She teaches gross anatomy, histology and embryology to undergraduate medical students.</p> <p>TG FATIMAH MURNIWATI TG MUDA, M.D., M.Sc. (Clin. Anat.), is an associate professor in the Faculty of Medicine, Medical Campus, Universiti Sultan Zainal Abidin Terengganu, Malaysia. She teaches gross anatomy, histology and embryology to undergraduate medical students.</p> <p>WAN NOR ARIFIN, M.B.B.S., M.Sc. (Med. Stat.), is a medical lecturer in the Unit of Biostatistics and Research Methodology, at the School of Medical Sciences, UniversitiSains Malaysia, Kelantan, Malaysia. He teaches biostatistics and research methodology to undergraduate medical and postgraduate students.</p> <p>MUHAMAD SAIFUL BAHRI YUSOFF, M.D., M.Sc., Ph.D. (Med. Educ.), is a senior medical lecturer and Head of the Department of Medical Education in the School of Medical Sciences, Health Campus, Universiti Sains Malaysia, Kelantan, Malaysia. He teaches psychometric assessment, educational research methodology and curriculum planning and development to postgraduate students and faculty members.</p> <p>Additional Supporting Information may be found in the online version of this article.</p> <hd id="AN0124968752-21">LITERATURE CITED</hd> <p>1 Al‐Hazimi A, Zaini R, Al‐Hyiani A, Hassan N, Gunaid A, Ponnamperuma G, Karunathilake I, Sue R, McAleer S, Davis M. 2004. Educational environment in traditional and innovative medical schools: A study in four undergraduate medical schools. Educ Health (Abingdon) 17 : 192 – 203.</p> <ulist> <item>2 AMA. 2008. American Medical Association. Initiative to Transform Medical Education. Phase 3: Program Implementation. Recommendations for Optimizing the Medical Education Learning Environment. Final Report of the December 2007 Working Conferences. 1st Ed. Washington, DC: American Medical Association. 24 p. URL: http://med2.uc.edu/Libraries/Medical_Education_Documents/AMA_ITME_Project.sflb.ashx [accessed 15 July 2016]</item> <item>3 Arbuckle JL. 2010. IBM SPSS® Amos™ 19: User's GuideComputer Program. 1st Ed. Chicago, IL : SPSS Inc. 654 p.</item> <item>4 Arzuman H, Yusoff MS, Chit SP. 2010. Big Sib students' perceptions of the educational environment at the school of medical sciences, UniversitiSains Malaysia, using Dundee ready educational environment measure (DREEM) inventory. Malays J Med Sci 17 : 40 – 47.</item> <item>5 Baeten M, Kyndt E, Struyven K, Dochy F. 2010. Using student‐centred learning environments to stimulate deep approaches to learning: Factors encouraging or discouraging their effectiveness. Educ Res Rev 5 : 243 – 260.</item> <item>6 Bartholomew DJ, Knott M, Mostaki I, Galbraith JI. 2008. Analysis of Multivariate Social Science Data. 2nd Ed. Boca Raton, FL : Chapman &amp; Hall/CRC Press. 384 p.</item> <item>7 Bay BH, Ling EA. 2007. Teaching of anatomy in the new millennium. Singapore Med J 48 : 182 – 183.</item> <item>8 Bentler PM. 1990. Comparative fit indexes in structural models. Psychol Bull 107 : 238 – 246.</item> <item>9 Bentler PM, Bonett DG. 1980. Significance tests and goodness of fit in the analysis of covariance structures. Psychol Bull 88 : 588 – 606.</item> <item>10 Bergman EM, Prince KJ, Drukker J, van der Vleuten CP, Scherpbier AJ. 2008. How much anatomy is enough? Anat Sci Educ 1 : 184 – 188.</item> <item>11 Bergman EM, Sieben JM, Smailbegovic I, de Bruin AB, Scherpbier AJ, van der Vleuten CP. 2013. Constructive, collaborative, contextual, and self‐directed learning in surface anatomy education. Anat Sci Educ 6 : 114 – 124.</item> <item>12 Bland JM, Altman DG. 1997. Statistics notes: Cronbach's alpha. BMJ 314 : 572.</item> <item>13 Böckers A, Jerg‐Bretzke L, Lamp C, Brinkmann A, Traue HC, Böckers TM. 2010. The gross anatomy course: An analysis of its importance. Anat Sci Educ 3 : 3 – 11.</item> <item>14 Bollen KA. 1989. A new incremental fit index for general structural equation models. Socio Meth Res 17 : 303 – 316.</item> <item>15 Brown TA. 2006. CFA with equality constraints, multiple groups, and mean structures. In: Brown TA (Editor). Confirmatory Factor Analysis for Applied Research. 1st Ed. New York, NY : Guildford Press. p 236 – 319.</item> <item>16 Browne MW, Cudeck R. 1992. Alternative ways of assessing model fit. Socio Meth Res 21 : 230 – 258.</item> <item>17 Burleson SE, Thoron AC. 2014. Maslow's Hierarchy of Needs and Its Relation to Learning and Achievement. 1st Ed. Gainesville, FL: Agricultural Education and Communication Department, UF/IFAS Extension, University of Florida. 3 p. URL: http://edis.ifas.ufl.edu/wc159 [accessed 22 July 2016]</item> <item>18 Chan DS. 2003. Validation of the clinical learning environment inventory. Western J Nurs Res 25 : 519 – 532.</item> <item>19 Christophel DM. 1990. The relationships among teacher immediacy behaviors, student motivation, and learning. Comm Educ 39 : 323 – 340.</item> <item>20 Collins JP. 2008. Modern approaches to teaching and learning anatomy. BMJ 337 : a1310.</item> <item>21 Collins TJ, Given RL, Hulsebosch CE, Miller BT. 1994. Status of gross anatomy in the US and Canada: Dilemma for the 21st century. Clin Anat 7 : 275 – 296.</item> <item>22 Cook DA, Beckman TJ. 2006. Current concepts in validity and reliability for psychometric instruments: Theory and application. Am J Med 119 : 166.e7 – 166.e16.</item> <item>23 DeCoster J, Claypool HM. 2004. Data Analysis in SPSS. 1st Ed. Tuscaloosa, AL : University of Alabama. 59 p. URL: http://www.bama.ua.edu/~py602/spss%202005%2009-21.pdf [accessed 19 May 2016]</item> <item>24 Dent JA, Harden RM (Editors). 2013. A Practical Guide for Medical Teachers. 4th Ed. London, UK : Churchill Livingstone. 456 p.</item> <item>25 DeVon HA, Block ME, Moyle‐Wright P, Ernst DM, Hayden SJ, Lazzara DJ, Savoy SM, Kostas‐Polston E. 2007. Apsychometric toolbox for testing validity and reliability. J Nurs Scholarsh 39 : 155 – 164.</item> <item>26 Dickson JK, Morris G, Heron M. 2009. The importance of hand anatomy in the accident and emergency department: Assessment of hand anatomy knowledge in doctors in training. J Hand Surg Eur Vol 34 : 682 – 684.</item> <item>27 Downing SM, Haladyna TM. 2004. Validity threats: Overcoming interference with proposed interpretations of assessment data. Med Educ 38 : 327 – 333.</item> <item>28 Elizondo‐Omaña RE, Guzmán‐López S, García‐Rodríguez Mde L. 2005. Dissection as a teaching tool: Past, present, and future. Anat Rec 285B : 11 – 15.</item> <item>29 Estai M, Bunt S. 2016. Best teaching practices in anatomy education: A critical review. Ann Anat 208 : 151 – 157.</item> <item>30 Field A. 2009. Discovering Statistics Using SPSS. 3rd Ed. London, UK : Sage Publications Ltd. 749 p.</item> <item>31 Fraser BJ. 1998. Classroom environment instruments: Development, validity and applications. Learn Environ Res 1 : 7 – 34.</item> <item>32 Ganguly PK. 2010. Teaching and learning of anatomy in the 21st century: Direction and the Strategies. Open Med Edu J 3 : 5 – 10.</item> <item>33 Haynes SN, Richard D, Kubany ES. 1995. Content validity in psychological assessment: A functional approach to concepts and methods. Psychol Assess 7 : 238 – 247.</item> <item>34 Heylings DJ. 2002. Anatomy 1999–2000: The curriculum, who teaches it and how? Med Educ 36 : 702 – 710.</item> <item>35 Hsu CC, Sandford BA. 2007. The Delphi technique: Making sense of consensus. Practical Assess Res Eval 12 : 1 – 8.</item> <item>36 Hutchinson L. 2003. Educational environment. BMJ 326 : 810 – 812.</item> <item>37 Johnson EO, Charchanti AV, Troupis TG. 2012. Modernization of an anatomy class: From conceptualization to implementation. A case for integrated multimodal‐multidisciplinary teaching. Anat Sci Educ 5 : 354 – 366.</item> <item>38 Jöreskog K, Sörbom D. 1984. LISREL VI, Analysis of Linear Structural Relationships by Maximum Likelihood, Instrumental Variables, and Least Squares Methods. 3rd Ed. Moorsville, IN : Scientific Software Inc. 275 p.</item> <item>39 Kagan II. 2002. Traditions and peculiarities of clinical anatomy education in Russia. Clin Anat 15 : 152 – 156.</item> <item>40 Kulik JA. 2001. Student ratings: Validity, utility, and controversy. New Dir Inst Res 109 : 9 – 25.</item> <item>41 Lim VK. 2008. Medical education in Malaysia. Med Teach 30 : 119 – 123.</item> <item>42 Linstone HA, Turoff M (Editors). 2002. The Delphi Method: Techniques and Applications. 2nd Ed. Boston, MA : Addison‐Wesley Educational Publishers Inc. 621 p.</item> <item>43 Lynn MR. 1986. Determination and quantification of content validity. Nurs Res 35 : 382 – 386.</item> <item>44 MacDougall M. 2011. Moving beyond the nuts and bolts of score reliability in medical education: Some valuable lessons from measurement theory. AdvAppl Stat Sci 6 : 643 – 664.</item> <item>45 Marsh HW, Hocevar D. 1985. Application of confirmatory factor analysis to the study of self‐concept: First‐and higher order factor models and their invariance across groups. Psychol Bull 97 : 562 – 582.</item> <item>46 McCuskey RS, Carmichael SW, Kirch DG. 2005. The importance of anatomy in health professions education and the shortage of qualified educators. Acad Med 80 : 349 – 351.</item> <item>47 McKeown PP, Heylings DJ, Stevenson M, McKelvey KJ, Nixon JR, McCluskey DR. 2003. The impact of curricular change on medical students' knowledge of anatomy. Med Educ 37 : 954 – 961.</item> <item>48 McLachlan JC, Patten D. 2006. Anatomy teaching: Ghosts of the past, present and future. Med Educ 40 : 243 – 253.</item> <item>49 Mosier CI. 1947. A critical examination of the concepts of face validity. Educ Psychol Meas 7 : 191 – 205.</item> <item>50 Muijs D. 2006. Measuring teacher effectiveness: Some methodological reflections. Educ Res Eval 12 : 53 – 74.</item> <item>51 Osborne JW, Costello AB. 2009. Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Pan Pac Manag Rev 12 : 131 – 146.</item> <item>52 Pabst R, Rothkötter HJ. 1997. Retrospective evaluation of undergraduate medical education by doctors at the end of their residency time in hospitals: Consequences for the anatomical curriculum. Anat Rec 249 : 431 – 434.</item> <item>53 Pandey P, Zimitat C. 2007. Medical students' learning of anatomy: Memorisation, understanding and visualisation. Med Educ 41 : 7 – 14.</item> <item>54 Papa V, Vaccarezza M. 2013. Teaching anatomy in the XXI century: New aspects and pitfalls. Sci World J 2013 : 310348.</item> <item>55 Parker LM. 2002. Anatomical dissection: Why are we cutting it out? Dissection in undergraduate teaching. ANZ J Surg 72 : 910 – 912.</item> <item>56 Patel KM, Moxham BJ. 2008. The relationships between learning outcomes and methods of teaching anatomy as perceived by professional anatomists. Clin Anat 21 : 182 – 189.</item> <item>57 Pimparyon P, Caleer SM, Pemba S, Roff S. 2000. Educational environment, student approaches to learning and academic achievement in a Thai nursing school. Med Teach 22 : 359 – 364.</item> <item>58 Polit DF, Beck CT. 2004. Nursing Research: Principles and Methods. 7th Ed. Philadelphia, PA : Lippincott Williams &amp; Wilkins. 784 p.</item> <item>59 Polit DF, Beck CT, Owen SV. 2007. Is the CVI an acceptable indicator of content validity? Appraisal and recommendations. Res Nurs Health 30 : 459 – 467.</item> <item>60 Pornprasertmanit S, Miller P, Schoemann A, Rosseel Y. 2016. SemTools: Useful tools for structural equation modeling. Version 0.4‐14. Lawrence, KS: University of Kansas. 131 p. URL: https://cran.r-project.org/web/packages/semTools/semTools.pdf [accessed 16 September 2016]</item> <item>61 Prince KJ, Scherpbier AJ, van Mameren H, Drukker J, van der Vleuten CP. 2005. Do students have sufficient knowledge of clinical anatomy? Med Educ 39 : 326 – 332.</item> <item>62 Prince KJ, van Mameren H, Hylkema N, Drukker J, Scherpbier AJ, van der Vleuten CP. 2003. Does problem‐based learning lead to deficiencies in basic science knowledge? An empirical case on anatomy. Med Educ 37 : 15 – 21.</item> <item>63 Raftery AT. 2006. Anatomy teaching in the UK. Surgery (Oxford) 25 : 1 – 2.</item> <item>64 Raykov T. 1998. Coefficient alpha and composite reliability with interrelated nonhomogeneous items. Appl Psychol Meas 22 : 375 – 385.</item> <item>65 Raykov T. 2001. Estimation of congeneric scale reliability using covariance structure analysis with nonlinear constraints. Br J Math Stat Psychol 54 : 315 – 323.</item> <item>66 Rios J, Wells C. 2014. Validity evidence based on internal structure. Psicothema 26 : 108 – 116.</item> <item>67 Roff S, McAleer S. 2001. What is educational climate? Med Teach 23 : 333 – 334.</item> <item>68 Roff S, McAleer S, Harden RM, Al‐Qahtani M, Ahmed AU, Deza H, Groenen G, Primparyon P. 1997. Development and validation of the Dundee ready education environment measure (DREEM). Med Teach 19 : 295 – 299.</item> <item>69 Roscoe JT. 1975. Fundamental Research Statistics for the Behavioural Sciences. 2nd Ed. New York, NY : Holt Rinehart &amp; Winston. 483 p.</item> <item>70 Spielmann PM, Oliver CW. 2005. The carpal bones: A basic test of medical students' and junior doctors' knowledge of anatomy. Surgeon 3 : 257 – 259.</item> <item>71 Stevens JP. 2009. Applied Multivariate Statistics for the Social Sciences. 5th Ed. New York, NY : Routledge. 664 p.</item> <item>72 Streiner LD, Norman GR. 2008. Health Measurement Scales: A Practical Guide to Their Development and Use. 4th Ed. New York, NY : Oxford University Press. 450 p.</item> <item>73 Tibrewal S. 2006. The anatomy knowledge of surgical trainees: The trainer's view. Bull Roy Coll Surg Engl 88 : 240 – 242.</item> <item>74 Trelease RB. 2016. From chalkboard, slides, and paper to e‐learning: How computing technologies have transformed anatomical sciences education. Anat Sci Educ 9 : 583 – 602.</item> <item>75 Turney BW. 2007. Anatomy in a modern medical curriculum. Ann R Coll Surg Engl 89 : 104 – 107.</item> <item>76 Varma R, Tiyagi E, Gupta JK. 2005. Determining the quality of educational climate across multiple undergraduate teaching sites using the DREEM inventory. BMC Med Educ 5 : 8.</item> <item>77 Winkelmann A. 2007. Anatomical dissection as a teaching method in medical school: A review of the evidence. Med Educ 41 : 15 – 22.</item> <item>78 Yusoff MSB, Jaa'far R, Arzuman H, Arifin WN, Mat Pa MN. 2013. Perceptions of medical students regarding educational climate at different phases of medical training in a Malaysian medical school. Educ Med J 5 :e30–e41.</item> </ulist> <p>Graph: The flowchart of the research methodology. AEEMI, Anatomy Education Environment Measurement Inventory; I‐CVI, item‐level content validity index; S‐CVI/Avg, scale‐level content validity index averaging method; I‐CI, item‐level clarity index; S‐CI/Avg, scale‐level clarity index averaging method; EFA, exploratory factor analysis; CFA, confirmatory factor analysis.</p> <p>Graph: Supporting Information</p> <aug> <p>By Siti Nurma Hanim Hadie; Asma' Hassan; Zul Izhar Mohd Ismail; Mohd Asnizam Asari; Aaijaz Ahmed Khan; Fazlina Kasim; Nurul Aiman Mohd Yusof; Husnaida Abdul Manan@Sulong; Tg Fatimah Murniwati Tg Muda; Wan Nor Arifin and Muhamad Saiful Bahri Yusoff</p> </aug> <nolink nlid="nl1" bibid="bib67" firstref="ref1"></nolink> <nolink nlid="nl2" bibid="bib2" firstref="ref2"></nolink> <nolink nlid="nl3" bibid="bib36" firstref="ref3"></nolink> <nolink nlid="nl4" bibid="bib17" firstref="ref4"></nolink> <nolink nlid="nl5" bibid="bib57" firstref="ref6"></nolink> <nolink nlid="nl6" bibid="bib5" firstref="ref7"></nolink> <nolink nlid="nl7" 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| Header | DbId: eric DbLabel: ERIC An: EJ1153168 AccessLevel: 3 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Anatomy Education Environment Measurement Inventory: A Valid Tool to Measure the Anatomy Learning Environment – Name: Language Label: Language Group: Lang Data: English – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Hadie%2C+Siti+Nurma+Hanim%22">Hadie, Siti Nurma Hanim</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0001-9046-9379">0000-0001-9046-9379</externalLink>)<br /><searchLink fieldCode="AR" term="%22Hassan%2C+Asma'%22">Hassan, Asma'</searchLink><br /><searchLink fieldCode="AR" term="%22Ismail%2C+Zul+Izhar+Mohd%22">Ismail, Zul Izhar Mohd</searchLink><br /><searchLink fieldCode="AR" term="%22Asari%2C+Mohd+Asnizam%22">Asari, Mohd Asnizam</searchLink><br /><searchLink fieldCode="AR" term="%22Khan%2C+Aaijaz+Ahm%22">Khan, Aaijaz Ahm</searchLink><br /><searchLink fieldCode="AR" term="%22Kasim%2C+Fazlina%22">Kasim, Fazlina</searchLink><br /><searchLink fieldCode="AR" term="%22Yusof%2C+Nurul+Aiman+Mohd%22">Yusof, Nurul Aiman Mohd</searchLink><br /><searchLink fieldCode="AR" term="%22Manan%40Sulong%2C+Husnaida+Abdul%22">Manan@Sulong, Husnaida Abdul</searchLink><br /><searchLink fieldCode="AR" term="%22Tg+Muda%2C+Tg+Fatimah+Murniwati%22">Tg Muda, Tg Fatimah Murniwati</searchLink><br /><searchLink fieldCode="AR" term="%22Arifin%2C+Wan+Nor%22">Arifin, Wan Nor</searchLink><br /><searchLink fieldCode="AR" term="%22Yusoff%2C+Muhamad+Saiful+Bahri%22">Yusoff, Muhamad Saiful Bahri</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="SO" term="%22Anatomical+Sciences+Education%22"><i>Anatomical Sciences Education</i></searchLink>. Sep-Oct 2017 10(5):423-432. – Name: Avail Label: Availability Group: Avail Data: Wiley-Blackwell. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA – Name: PeerReviewed Label: Peer Reviewed Group: SrcInfo Data: Y – Name: Pages Label: Page Count Group: Src Data: 10 – Name: DatePubCY Label: Publication Date Group: Date Data: 2017 – Name: TypeDocument Label: Document Type Group: TypDoc Data: Journal Articles<br />Reports - Research – Name: Audience Label: Education Level Group: Audnce Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink> – Name: Subject Label: Descriptors Group: Su Data: <searchLink fieldCode="DE" term="%22Anatomy%22">Anatomy</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Environment%22">Educational Environment</searchLink><br /><searchLink fieldCode="DE" term="%22Measures+%28Individuals%29%22">Measures (Individuals)</searchLink><br /><searchLink fieldCode="DE" term="%22Delphi+Technique%22">Delphi Technique</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Attitudes%22">Student Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+Students%22">Medical Students</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+Schools%22">Medical Schools</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Content+Validity%22">Content Validity</searchLink><br /><searchLink fieldCode="DE" term="%22Test+Reliability%22">Test Reliability</searchLink><br /><searchLink fieldCode="DE" term="%22Factor+Analysis%22">Factor Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Goodness+of+Fit%22">Goodness of Fit</searchLink><br /><searchLink fieldCode="DE" term="%22Psychometrics%22">Psychometrics</searchLink> – Name: Subject Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Malaysia%22">Malaysia</searchLink> – Name: DOI Label: DOI Group: ID Data: 10.1002/ase.1683 – Name: ISSN Label: ISSN Group: ISSN Data: 1935-9772 – Name: Abstract Label: Abstract Group: Ab Data: Students' perceptions of the education environment influence their learning. Ever since the major medical curriculum reform, anatomy education has undergone several changes in terms of its curriculum, teaching modalities, learning resources, and assessment methods. By measuring students' perceptions concerning anatomy education environment, valuable information can be obtained to facilitate improvements in teaching and learning. Hence, it is important to use a valid inventory that specifically measures attributes of the anatomy education environment. In this study, a new 11-factor, 132-items Anatomy Education Environment Measurement Inventory (AEEMI) was developed using Delphi technique and was validated in a Malaysian public medical school. The inventory was found to have satisfactory content evidence (scale-level content validity index [total] = 0.646); good response process evidence (scale-level face validity index [total] = 0.867); and acceptable to high internal consistency, with the Raykov composite reliability estimates of the six factors are in the range of 0.604-0.876. The best fit model of the AEEMI is achieved with six domains and 25 items (X[superscript 2] = 415.67, P < 0.001, ChiSq/df = 1.63, RMSEA = 0.045, GFI = 0.905, CFI = 0.937, NFI = 0.854, TLI = 0.926). Hence, AEEMI was proven to have good psychometric properties, and thus could be used to measure the anatomy education environment in Malaysia. A concerted collaboration should be initiated toward developing a valid universal tool that, using the methods outlined in this study, measures the anatomy education environment across different institutions and countries. – Name: AbstractInfo Label: Abstractor Group: Ab Data: As Provided – Name: DateEntry Label: Entry Date Group: Date Data: 2017 – Name: AN Label: Accession Number Group: ID Data: EJ1153168 |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/ase.1683 Languages: – Text: English PhysicalDescription: Pagination: PageCount: 10 StartPage: 423 Subjects: – SubjectFull: Anatomy Type: general – SubjectFull: Educational Environment Type: general – SubjectFull: Measures (Individuals) Type: general – SubjectFull: Delphi Technique Type: general – SubjectFull: Student Attitudes Type: general – SubjectFull: Medical Students Type: general – SubjectFull: Medical Schools Type: general – SubjectFull: Foreign Countries Type: general – SubjectFull: Content Validity Type: general – SubjectFull: Test Reliability Type: general – SubjectFull: Factor Analysis Type: general – SubjectFull: Goodness of Fit Type: general – SubjectFull: Psychometrics Type: general – SubjectFull: Malaysia Type: general Titles: – TitleFull: Anatomy Education Environment Measurement Inventory: A Valid Tool to Measure the Anatomy Learning Environment Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Hadie, Siti Nurma Hanim – PersonEntity: Name: NameFull: Hassan, Asma' – PersonEntity: Name: NameFull: Ismail, Zul Izhar Mohd – PersonEntity: Name: NameFull: Asari, Mohd Asnizam – PersonEntity: Name: NameFull: Khan, Aaijaz Ahm – PersonEntity: Name: NameFull: Kasim, Fazlina – PersonEntity: Name: NameFull: Yusof, Nurul Aiman Mohd – PersonEntity: Name: NameFull: Manan@Sulong, Husnaida Abdul – PersonEntity: Name: NameFull: Tg Muda, Tg Fatimah Murniwati – PersonEntity: Name: NameFull: Arifin, Wan Nor – PersonEntity: Name: NameFull: Yusoff, Muhamad Saiful Bahri IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2017 Identifiers: – Type: issn-print Value: 1935-9772 Numbering: – Type: volume Value: 10 – Type: issue Value: 5 Titles: – TitleFull: Anatomical Sciences Education Type: main |
| ResultId | 1 |
