April 2012 Volume 15 Number 2 - Educational Technology & Society

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6. After the students complete all the sessions, they can click the ‘test’ button to enter the KSAT computerized adaptive testing system (see Figure 7). 7. When a student completes the test, the computer screen will show an individual assessment report of his test results. The upper portion of the report includes the student’s basic information, the score and percentile of this test. The lower half includes the student’s learning records, test dates, test times, scores, the number of questions, and the recorded answers. Additionally, the report also lists details of the concepts tested in this unit, the diagnosis results, and online remedial materials of the math path (see Figure 8-9). Figure 8. KSAT concepts diagnostic report 1 Figure 9. KSAT concepts diagnostic report 2 Subsequently, the respective remedial instruction is implemented using online remedial materials of the math path. The U-learning math path remedial lesson is displayed in Figure 10. Figure 10. Animation clip of remedial lesson in the system 303
Participants and Experimental Procedure The participants of this study are elementary school fifth graders in Taiwan. Four classes are chosen to participate in this study, two classes are assigned as the experimental group randomly, and the other two are assigned as the control group. There are originally 122 students in the four classes. However, 4 students are unable to complete the tests; thus, the effective sampling population is reduced to 118 students, with 59 in the experimental group and 59 in the control group. The experimental group is taught using “the adaptive U-learning math path learning activity,” while the control group learned using “the traditional paper-and-pencil based math path learning activity”. The experiment process is shown in Table 2: Process (time) Test 1 (one lesson) Teaching activities (six lessons) Test 2 (one lesson) Remedial activities (one lesson) Test 3 (one lesson) Mathematical connection ability questionnaire (twenty minutes) Table 2. The experiment process Experimental group computerized adaptive diagnostic test adaptive U-learning math path teaching process computerized adaptive diagnostic test adaptive U-learning remedial lessons computerized adaptive diagnostic test paper-and-pencil test Control group computerized adaptive diagnostic test traditional math path teaching process computerized adaptive diagnostic test traditional remedial lessons computerized adaptive diagnostic test paper-and-pencil test As shown in Table 2, there are three computerized diagnostic tests of “looking for patterns” unit and a mathematical connection ability questionnaire used as evaluation tools. The three tests are Test1, Test2 and Test3, each with 30 questions. They are parallel forms with a Cronbach α reliability coefficient of 0.75, indicating that the difficulty rates of the test questions are between 31.3% and 96.0%. The coefficient of determination ranged between 0.3 and 0.5, and the validity is assessed by field experts. In order to combine ubiquitous learning, campus math path and the knowledge structure based adaptive testing system. Test1, Test2 and Test3 are all administered by KSAT. The adaptive testing algorithm of KSAT is based on the students’ item structure. This structure is estimated by ordering theory (Airasian & Bart, 1973). As shown in Figure 11, if the subject gets a top skill (item C) correct then it is inferred that he or she also understands its prerequisites (items F, G, H, I). This algorithm can predict students’ profiles using fewer items than in original paper-and-pencil based tests. Figure 11. The students’ item structure The mathematical connection ability questionnaire is developed based on mathematical connection competence indicators of Grade 1-9 Curriculum Guidelines in Taiwan (Ministry of Education of the R.O.C., 2009). There are 3 dimensions in this questionnaire: the first dimension assesses the students’ abilities to connect mathematics to real 304
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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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Page 263 and 264: on-site to finally achieve a meanin
Page 265 and 266: Table 1. Digital game designers and
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Page 269 and 270: Phase Methods Visitor data collecti
Page 271 and 272: operate the game without the help o
Page 273 and 274: Visitors (end users) must be heard.
Page 275 and 276: Islas Sedano, C., Pawlowski, J., Su
Page 277 and 278: part of something larger than the s
Page 279 and 280: Previous studies have developed rel
Page 281 and 282: Technology Acceptance. The 10 items
Page 283 and 284: Table 4. Model Fit Indices Model χ
Page 285 and 286: In the final path model of set 1, t
Page 287 and 288: Discussion Differing from prior stu
Page 289 and 290: Haythornthwaite, C., Kazmer, M. M.,
Page 291 and 292: Ge, Z.-G. (2012). Cyber Asynchronou
Page 293 and 294: college of a university situated in
Page 295 and 296: Table 3 shows us the following info
Page 297 and 298: Appendix B shows Class 1’s respon
Page 299 and 300: increase one’s ability to process
Page 301 and 302: Appendix A Responses concerning syn
Page 303 and 304: Shih, S.-C., Kuo, B.-C., & Liu, Y.-
Page 305 and 306: Adaptive U-learning Math Path Syste
Page 307: Figure 4. Online tutorial courses o
Page 311 and 312: the influence of Test1 scores, an e
Page 313 and 314: Hall, T., & Bannon, L. (2006). Desi
Page 315 and 316: (Hofer & Pintrich, 1997; Liu, Lin &
Page 317 and 318: � Through online peer assessment,
Page 319 and 320: elativism.” High Internet self-ef
Page 321 and 322: Peng, H., Tsai, C.-C., & Wu, Y.-T.
Page 323 and 324: Since game-based learning has been
Page 325 and 326: The second reason is about the sust
Page 327 and 328: Methods Figure 5. Quest NPCs provid
Page 329 and 330: These differences indicated that pa
Page 331 and 332: quests further involves students’
Page 333 and 334: Chang, I.-H. (2012). The Effect of
Page 335 and 336: (1) Vision, planning and management
Page 337 and 338: Based on an examination of the lite
Page 339 and 340: Table 2. Analysis of reliability an
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 351 and 352: Research question For the purpose o
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
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Hsu, Y.-C., Ho, H. N. J., Tsai, C.-
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domains. Five research questions we
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Research sample groups (4) Faculty
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13. Policies, Social Culture Impact
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Non-Specified Others Engineering &
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(AR = -2.1) (n = 7) 2. Non-specifie
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(n): Total number of articles Resea
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Compared to the publications in 200
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Pedagogical Content Knowledge (TPAC
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