April 2012 Volume 15 Number 2 - Educational Technology & Society

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Educational Level BA or BS 97 16.0% BA or BS (from teachers college or normal university) 338 55.9% M.A. or M.Ed. 165 27.3% Ph.D. or Ed.D. Position 1 0.2 % Mentor Teacher 256 42.3% Specialist Teacher 69 11.4% Administrative Head 190 31.4% Director 88 14.5% * Numbers and percentages in the categories may not total 100 due to some missing data. Instrumentation and variables The Principals’ Technological leadership Instrument was conceptualized as five interrelated dimensions: (1) vision, planning and management (e.g., clearly articulates a shared vision for technology use in the school); (2) staff development and training (e.g., encourages technology in-service training); (3) technological and infrastructure support (e.g., ensures appropriate technology facilities); (4) evaluation and research (e.g., considers effective technology use as one performance assessment component of instructional staff); and (5) interpersonal and communication skills (e.g., demonstrates an understanding of technology needs and concerns of faculty). The Teachers’ Technological Literacy Instrument comprised four dimensions: (1) hardware and software operation (e.g., understands the functions of basic components of computer hardware); (2) law and ethics (e.g., understands the meaning of ownership and publication, and show respect to intellectual property rights); (3) technological integration (e.g., understands the benefits and scope for applying computer to teaching); and (4) management and assessment (e.g., possesses the ability in using teaching software and evaluating online teaching materials). The Teachers’ Teaching Effectiveness Instrument included five dimensions: (1) teaching-material preparation (e.g., be comprehensively familiar with the content of the unit to be taught before teaching); (2) applications of teaching skills (e.g., continuously attracts students’ attention by changing activities during class); (3) classroom management (e.g., continually compliments and encourages students for their progress); (4) teaching assessment (e.g., effectively implements various evaluation methods according to teaching needs); and (5) self-efficacy and belief (e.g., has a positive influence on students’ learning achievements). These three instruments comprised 101 Likert-type items on 5-point scales. A response of “1” indicated that the teacher strongly disagreed with the statement on the scale, and a response of “5” indicated that the teacher strongly agreed with the statement on the scale. A pilot study was conducted with approximately 204 teachers and school administrators to improve the instruments’ reliability and validity. The Cronbach’s alpha coefficients (shown in parentheses and see also table 2) were calculated for each scale: vision, planning and management (.96); staff development and training (.90); technological and infrastructure support (.92); evaluation and research (.96); interpersonal and communication skills (.93); hardware and software operation (.94); law and ethics (.90); technological integration (.91); management and assessment (.90); teachingmaterial preparation (.92); applications of teaching skills (.88); classroom management (.93); teaching assessment (.89); and self-efficacy and belief (.95). In addition to reliability analysis, construct validity tests of the aforementioned three instruments were performed. Five factors were extracted using Varimax rotation from The Principals’ Technology Leadership Instrument. The variance factors were as follows: 21.148% (vision, planning and management), 15.858% (evaluation and research), 15.430% (technological and infrastructure support), 14.573% (interpersonal and communication skills), and 11.958% (staff development and training). The total explained variance of these five factors was 78.966%. Four factors were extracted using Varimax rotation from The Teachers’ Technology Literacy Instrument. The variance factors were as follows: 24.474% (hardware and software operation), 22.055% (technological integration), 13.304% (law and ethics), and 10.375% (management and assessment). The total explained variance of these four factors was 70.208%. Five factors were extracted using Varimax rotation from The Teachers’ Teaching Effectiveness Instrument. The variance factors were as follows: 22.082% (applications of teaching skills), 19.060% (self-efficacy and belief), 12.726% (teaching-material preparation), 11.314% (teaching assessment), and 10.029% (classroom management). The total explained variance of these five factors was 75.211% (see table 2). 333
Table 2. Analysis of reliability and validity Dimension Cronbach’s alpha coefficient Variance explained Vision, planning and management .96 21.148% Staff development and training .90 11.958% Technological and infrastructure support .92 15.430% Evaluation and research .96 15.858% Interpersonal and communication skills .93 14.573% Hardware and software operation .94 24.474% Law and ethics .90 13.304% Technological integration .91 22.055% Management and assessment .90 10.375% Teaching-material preparation .92 12.726% Applications of teaching skills .88 22.082% Classroom management .93 10.029% Teaching assessment .89 11.314% Self-efficacy and belief .95 19.060% Data analysis This research empirically investigated the relationships among principals’ technological leadership, teachers’ technological literacy, and teaching effectiveness and tested the structural equation model (SEM). SPSS was used to calculate scale reliabilities (the Cronbach’s alpha) and to perform factor analyses. The final SEM model was done with LISREL. Results SEM lets researchers simultaneously define and measure multidimensional constructs (e.g., principals’ technological leadership). The fit of the model to the data was assessed with SEM fit indices. The Chi-Square value was 271.97 with 74 degrees of freedom and significance (p=.00). The NFI, NNFI, PNFI, CFI, SRMR, GFI, AGFI and PGFI values were .98, .99, .80, .99, .043, .93, .90 and .66, respectively. The Critical N was 204.42. The results of these common fit indices (see table 3) clearly indicated that the model fit these observed data quite well. Table 3. Assessment of overall model fit Fit Indices Ideal fit index Results Degrees of Freedom=74 Absolute fit indices Chi-Square Not significant 271.97 (p=.00) GFI >.90 .93 AGFI >.90 .90 SRMR ≦.05 .043 Comparative fit indices NNFI >.90 .99 CFI >.90 .99 NFI >.90 .98 Parsimonious fit indices PNFI >.50 .80 PGFI >.50 .66 Critical N >200 204.42 After ensuring that the model fit the data, the standardized parameter estimates were considered in the model. As shown in Figure 2, the parameter estimates for the five constructs (i.e., vision, planning and management; staff development and training; technological and infrastructure support; research and evaluation; interpersonal and 334
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April 2012 Volume 15 Number 2
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Supporting Organizations Centre for
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Contextualizing a MALL: Practice De
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Kop, R. (2012). The Unexpected Conn
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Human mediation and information flo
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elevant information based on some k
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of learners. A search facilitated t
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information as human mediation mean
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Blau, I., & Barak, A. (2012). How D
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examined whether the readiness to p
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Table 5 presents the ANOVA for the
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However, in discussing a non-sensit
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deviations showed smaller variance,
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actual participation discussing sen
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Mesch, G., & Elgali, Z. (2009). Soc
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Although prior research on overall
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with a score of 39 and below as “
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Table 2 demonstrates mean scores an
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Discussion Although the recent Inte
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Furthermore, the most preferred pla
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MEB. (2009). Internete erisim proje
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Learning Management Systems (LMS) b
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practice and repetition with feedba
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Online peer assessment Peer assessm
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At an international conference on m
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� Ability to produce rich assessm
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Meishar-Tal, H., & Tal-Elhasid, E.
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Tsai, S. C. (2012). Integration of
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order to decrease text complexity a
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matter how the learners’ aptitude
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If compared by programs, WP student
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mean F2F 4.64 4.52 4.35 4.44 *: p
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een analyzed and were compared with
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Chen, G.-D., Lee, J.-H., Wang, C.-Y
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and diverse cognitional and emotion
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Encourage and persuade students wit
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Materials and procedure Each studen
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The lower part of Figure 4 shows st
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Mayer, R. E., Sobko, K., & Mautone,
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that an item is answered correctly
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Table 1. Relative concepts frequenc
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The Account Management Module provi
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Experiment 1 and results Figure 7.
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Utilization of Test Item 36 33 30 2
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Utilization of Test Item 36 33 30 2
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0.065 0.877 (17.56) 0.938 (22.55) 0
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Hwang, G.J., Hsiao, C.L., & Tseng,
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the diverse needs of modern industr
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Figure 1. The framework of interdis
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Research Design Figure 3. Recommend
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friendly. 8. I feel the layout and
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satisfaction, and system acceptance
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Ozok, A. A., Fan, Q., & Norcio, A.
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than students in a conventional cla
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shown in Figure 2 to include the st
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(1996) Pleasure-Arousal-Dominance (
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Based on this connection, we consid
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Final dominance measurements were p
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student mood and thereby allow comp
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Sessink, O., Beeftink, H., Tramper,
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The rationale behind the video form
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usefulness of the movies and their
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case of the first two questions and
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this paper in order to evaluate the
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The survey questions Appendix A In
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E-training in organizations E-train
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efficacy regarding online training,
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Method Sample and procedure Figure
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0.874 which exceeded the recommende
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Even though the result does not con
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Brown, M., & Cudeck, R. (1993). Alt
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Wen, Y., Looi, C.-K., & Chen, W. (2
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when they are designing and impleme
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paper focuses on the first three st
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their self-esteem to be partners in
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Democratizing knowledge and symmetr
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1) Reading the article: At the star
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Effects of RCKI principle-based ped
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References Alexander, C. (1979). Th
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Valsamidis, S., Kontogiannis, S., K
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The Analog system (Yan et al., 1996
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First, the number of the sessions a
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BioLayout uses a modified version o
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As shown in figure 3, all metrics c
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Figure 7. The detailed results for
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Enright, A. J., van Dongen, S., Ouz
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Chu, S. K. W., Kwan, A. C. M., & Wa
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teachers, as well as collaboration
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from the students’ ratings appear
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Table 5 summarizes the students’
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eading blogs (i.e., reminders, easy
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Luehmann, A. L. (2008). Using blogg
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Uzunboylu et al. (2009) examined th
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System implementation Overview of M
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Methods Before the experiment, a mo
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too simple, incomplete, or they eve
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Comparisons of UMLS Questionnaire i
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already described may play an impor
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Parker, D., Manstead, A. S. R., Str
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Avci, U., & Askar, P. (2012). The C
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Literature review The related varia
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collected through Personal Informat
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Self-efficacy 92 5 21 13.37 3.726 W
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In this problem, intention was take
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References Ajjan, H., & Hartshorne,
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Tan, T.-H., Lin, M.-S., Chu, Y.-L.,
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Students perused the course materia
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problem. All articles were then sen
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tests, electronic tests are more li
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Students 10 and 11: My classmate Ed
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collection was also approved by all
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Ubiquitous Revision Seamless Collab
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Tai, Y. (2012). Contextualizing a M
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tasks were developed from task type
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experiences in this phase. Moreover
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test is administered again right af
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The collected data were analyzed wi
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Gorp, K. V., & Bogaert, N. (2006).
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4PL IRT model According to the numb
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examinee’s ability more accuratel
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would be more accurate if items j+1
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C�I or Change I�I) would be 0.2
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improved by rearrangement procedure
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Table 6. Repeated Measures ANOVA of
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Leppisaari, I., & Lee, O. (2012). M
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Selection of the virtual tool The t
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Environmental themes emerged strong
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Visualization of text (visual langu
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environments where visual technolog
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- Logging in to learning environmen
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McNaught, C., Lam, P. & Lam, S.L. (
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on-site to finally achieve a meanin
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Table 1. Digital game designers and
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worldviews are socio-cultural-histo
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Phase Methods Visitor data collecti
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operate the game without the help o
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Visitors (end users) must be heard.
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Islas Sedano, C., Pawlowski, J., Su
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part of something larger than the s
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Previous studies have developed rel
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Technology Acceptance. The 10 items
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Table 4. Model Fit Indices Model χ
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In the final path model of set 1, t
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Page 295 and 296: Table 3 shows us the following info
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Page 327 and 328: Methods Figure 5. Quest NPCs provid
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Page 333 and 334: Chang, I.-H. (2012). The Effect of
Page 335 and 336: (1) Vision, planning and management
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Page 341 and 342: λ10 - 0.69 0.83 ε5 14.50 * - 0.32
Page 343 and 344: Bailey, G. D. (1997). What technolo
Page 345 and 346: Stegall, P. (1998). The principal:
Page 347 and 348: instruction has studied the student
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Page 353 and 354: READI reliability To verify the con
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Page 357 and 358: The results of this study suggest t
Page 359 and 360: Hsu, Y.-C., Ho, H. N. J., Tsai, C.-
Page 361 and 362: domains. Five research questions we
Page 363 and 364: Research sample groups (4) Faculty
Page 365 and 366: 13. Policies, Social Culture Impact
Page 367 and 368: Non-Specified Others Engineering &
Page 369 and 370: (AR = -2.1) (n = 7) 2. Non-specifie
Page 371 and 372: (n): Total number of articles Resea
Page 373 and 374: Compared to the publications in 200
Page 375: Pedagogical Content Knowledge (TPAC
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