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Barret, R. L., & Schmidt, J. J. (1986). School counselor certification and supervision: Overlooked professional issues. Counselor Education and Supervision, 26, 50-55. Benigno, V., & Trentin, G. (2000). The evaluation of online courses. Journal of Computer Assisted Learning, 16 (3), 259-270. Bernard, J. M., & Goodyear, R. K. (2004). Fundamentals of clinical supervision (3 rd Ed.), Boston, MA: Pearson Education. Bobby, C. L., & Capone, L. III (2000). Understanding the implications of distance learning for accreditation and licensure of counselor preparation programs. In J. W. Bloom & G. R. Walz, (Eds.), Cybercounseling and cyberlearning: Strategies and resources for the millennium (pp. 361-377), Alexandria: American Counseling Association. Butler, S. K., & Constantine, M. G. (2006). Web-based peer supervision, collective self-esteem and case conceptualization ability in school counselor trainees. Professional School Counseling, 10, 146-152. Casey, J., Bloom, J. W., & Moan, E. R. (1994). Use of technology in counselor supervision. (Report number EDO- CG-94-00), Washington, DC: Office of Educational Research and Improvement. Chen, E. C., & Bernstein, B. L. (2000). Relations of complementarity and supervisory issues to supervisory working alliance: Comparative analysis of two cases. Journal of Counseling Psychology, 47 (4), 485-497. Christie, B. S. (1998). Distance clinical supervision in cyberspace: A qualitative study, Oregon State University, USA. Clingerman, T. L., & Bernard, J. M. (2004). An investigation of the use of email as a supplemental modality for clinical supervision. Counselor Education & Supervision, 44 (2), 82-95. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2 nd Ed.), Hillsdale, NJ: Lawrence Erlbaum. Davies, R. S., & Mendenhall, R. (1998). Evaluation comparison of online and classroom instruction for HEPE 129 – Fitness and lifestyle management course, retrieved March 2, 2009, from http://www.eric.ed.gov/ERICWebPortal/ contentdelivery/servlet/ERICServlet?accno=ED427752. DeBourgh, G. A. (1999). Technology is the tool, teaching is the task: Student satisfaction in distance learning. In J. Price, J. Willis, D. A. Willis, M. Jost & S. Boger-Mehall (Eds.), Proceedings of Society for Information Technology and Teacher Education International Conference (pp. 131-137). Chesapeake, VA: AACE. Efstation, J. F., Patton, M. J., & Kardash C. M. (1990). Measuring the working alliance in counselor supervision. Journal of Counseling Psychology, 37 (3), 322-329. Friedlander, M. L. & Ward, L. G. (1984). Development and validation of the supervisory styles inventory. Journal of Counseling Psychology, 31, 541-557. Gamon, D., Sorlie, T., Bergvik, S., & Hoifodt, T. S. (1998). Psychotherapy supervision conducted via videoconferencing: A qualitative study of users’ experiences. Nordic Journal of Psychiatry, 52 (5), 411-421. Gold, P.B. (1993). The Supervisory Working Alliance Inventory: A cross-validated study of the factorial structure. In K. D. Multon (Chair), The working alliance in counselor supervision, Symposium conducted at the 101st Annual Convention of the American Psychological Association, Toronto, Ontario, Canada. Graf, N. M., & Stebnicki, M. A. (2002). Using e-mail for clinical supervision in practicum: A qualitative analysis. Journal of Rehabilitation, 68 (3), 41-49. Hara, N., Bonk, C. J., & Angeli, C. (2000). Content analysis of online discussion in an applied educational psychology course. Instructional Science, 28, 115-152. Hayes, B. G., & Robinson, E. H. (2000). Assessing counselor education students’ attitudes toward computers and multimedia instruction. Journal of Humanistic Counseling, Education and Development, 38 (3), 132-141. Henderson, P. (1994). Supervision of school counselors (Report No. EDO-CG-94-21), Washington, DC: Office of Educational Research and Improvement. Holloway, E. L., & Wampold, B. E. (1983). Patterns of verbal behaviors and judgments of satisfaction in the supervision interview. Journal of Counseling Psychology, 30, 227-234. 305
Janoff, D. S., & Schoenholtz-Read, J. (1999). Group supervision meets technology: A model for computer-mediated group training at a distance. International Journal of Group Psychotherapy, 49 (2), 255 - 273. Kahn, B. B. (1999). Priorities and practices in field supervision of school counseling students. Professional School Counseling, 3 (2), 128-137. Kjosness, J. (2002). On the net 2002: Social work, Boston: Allyn & Bacon. Ladany, N., Ellis, M. V., & Friedlander, M. L. (1999). The supervisory working alliance, trainee self-efficacy, and satisfaction. Journal of Counseling and Development, 77, 447-455. Ladany, N., Hill, C. E., & Nutt, E. A. (2004). Supervision questionnaire. In J. M. Bernard & R. K. Goodyear (Eds.), Fundamentals of clinical supervision (3 rd Ed.), Boston: Pearson. Ladany, N., Lehrman-Waterman, D., Molinaro, M., & Wolgast, B. (1999). Psychotherapy supervisor ethical practices: Adherence to guidelines, the supervisory working alliance, and supervisee satisfaction. Counseling Psychologist, 27 (3), 443-475. Lambert, M. E., Hedlund, J. L., & Vieweg, B. W. (1990). Computer simulations in mental health education: Current status. Computers in Human Services, 7 (3-4), 211-229. Larson, D. L., Attkisson, C. C., Hargreaves, W. A., & Nguyen, T. D. (1979). Assessment of client/patient satisfaction: Development of a general scale. Evaluation and Program Planning, 2,197-207. Myrick, R. D., & Sabella, R. A. (1995). Cyberspace: New place for counselor supervision. Elementary School Guidance and Counseling, 30 (1), 35-45. Nelson, M. D., & Johnson, P. (1999). School counselors as supervisors: An integrated approach for supervising school counseling interns. Counselor Education and Supervision, 39, 89-100. Olson, M. M., Russell, C. S., & White, M. B. (2001). Technological implications for clinical supervision and practice, The Clinical Supervisor, 20 (2), 201-215. Patton, M. J., & Kivlighan, D. M. (1997). Relevance of the supervisory alliance to the counseling alliance and to treatment adherence in counselor training. Journal of Counseling Psychology, 44 (1), 108-115. Roberts, R. L., Powell, B. M., & Fraker, F. L. (2002). The effect of technology-mediated group supervision on attitudes toward use of technology and satisfaction with supervision among school counseling interns. Paper presented at the American Counseling Association Conference, March, New Orleans, USA. Salas, E., Kosarzycki, M. P., Burke, C. S., Fiore, S. M., & Stone, D. L. (2002). Emerging themes in distance learning research and practice: Some food for thought. International Journal of Management Reviews, 4 (2), 135-153. Smith, S. B. (1999). The effectiveness of traditional instructional methods in an online learning environment, Doctoral dissertation, Las Vegas, USA: University of Nevada. Wilczenski, F. L., & Coomey, S. M. (2006). Cyber-communication: Finding its place in school counseling practice, education, and professional development. Professional School Counseling, 9 (4), 327-331. Young, J. R. (2002). “Hybrid” teaching seeks to end the divide between traditional and online instruction. Chronicle of Higher Education, retrieved March 20, 2009 from http://chronicle.com/free/v48/i28/28a03301.htm. 306
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April 2009 Volume 12 Number 2
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Abstracting and Indexing Educationa
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Engaging students in multimedia-med
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this study discusses computer-based
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Sampling for preliminary study One
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Part 2 Pearson correlation .349** 1
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Figure 1. Box and whisker plot of t
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characteristics and learning styles
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However, critical reflection and in
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novels, so they collected any relat
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1. Theories of teaching: Comments m
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grammatical errors and basic writin
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Ho, B., & Richards, J. C. (1993). R
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Hwang, K.-A., & Yang, C.-H. (2009).
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e deduced from the Affective Domain
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Detection procedure Figure 1 shows
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avoided. Image processing is perfor
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falling asleep) as defined in this
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classmates or left their seats duri
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help teachers to recognize the lear
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Hsieh, P.-H., & Dwyer, F. (2009). T
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significant comprehension effects o
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Treatment 3 (keyword group): Studen
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Criteria of achievement measures Th
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esults. A correlational analysis de
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A 2 x 1 ANOVA analyzed the effect o
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References Aragon, S. R. (2004). In
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Raphael, T. (1982). Improving quest
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educing maintenance costs. The cont
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Synchronization functions According
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inconsistency) and navigate directl
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the suitability of the instructiona
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Design of manipulation process The
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Table 1: Comparative analysis of au
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the convenience of mobile-based ass
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According to evaluation result, the
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Tan, O. S., Parsons, R. D., Hinson,
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At a deeper level, though, there wa
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theoretical assumptions. Two theore
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The students were not going to have
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slightly different. The group who c
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every item, not giving any result.
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edited and presented to the class u
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Figure 10. Screen captures from the
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Some of the concerns that emerge fr
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Ajayi, L. (2009). An Exploration of
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As a result of the confluence of di
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peers (Schellens et al. 2005). Sche
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The integration of discussion board
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ecause the technology allowed the p
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The pre-service teachers perceived
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Furthermore, the study demonstrated
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Schellens, T., van Keer, H., & Valc
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McKean, 2003). Instructors will see
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program at The Ohio State Universit
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Knowledge and skills of developing
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their monthly reflections or assign
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Bull, K., Montgomery, D., Overton,
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frustrating the student). ITSs make
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• Link removal - advanced student
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Expert Module Expert Module’s mai
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Based on the questionnaire results
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students were told that their perfo
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thirds of the interviewed students
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Throughout the semester, students i
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human teacher or question developer
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To test the learning effectiveness
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APPENDIX A Computer Science and Sof
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Thus, the use of computers changes
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Specifically, two objectives were p
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Nonetheless, both teachers assign a
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48% 35% 53% similar similar 69% 42%
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Table 4: Students’ attitudes Stat
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activities. Specifically, the histo
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Huang, Y.-M., Huang, T.-C., Wang, K
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• Could recommended learning sequ
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Analysis of sequences prediction me
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Figure 4. The sorting of learning s
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The figures 5a and 5b illustrate th
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Learning sequence recommendation sy
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In this study, forty subjects were
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The potential for LSRS to promote l
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They pointed out that LSRS helped t
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Cover, T. M., & Thomas, J. A. (1991
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Related Efforts An Internet forum i
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with handheld devices and they were
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agent would direct learners to a le
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Mobile RSS Aggregator In order to s
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learning, such as posting question
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With novel technological support, m
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Shen, L., Wang, M., & Shen, R. (200
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as an ‘affective loop’, which r
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Figure 2 is an example of two-dimen
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preference was gathered through dat
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compute the heart rate (HR) as a fu
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sessions. Of all the 18 learning se
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Burleson, W., Picard, R. W., Perlin
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Wu, C.-C., & Lai, C.Y. (2009). Wire
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The wireless handheld learning envi
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the lengthiness of the scales, whic
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Nursing dictionary We constructed a
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them. The computers were networked
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“The major difference was that I
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questionnaire. We do not consider t
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Faruque, F., Hewlett, P. O., Wyatt,
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etween a user and the system. Addit
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Figure 2. A concept map representin
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C5.0 can help teachers to generate
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that a selected programming exercis
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differences between our system and
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1(students can complete without any
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The PADS sometimes assigned very di
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Corno, L. (2000). Looking at Homewo
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Hwang, W.-Y., Hsu, J.-L., Tretiakov
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listed these functions as allowing
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In the research presented in this a
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Research Tools Web-based learning e
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Table 1. Operational definitions of
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action, interaction, and outeractio
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for them was getting the answer as
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Table 6 shows the learners’ prefe
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Bell, P., & Winn, W. (2000). Distri
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Askar, P., & Altun, A. (2009). CogS
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elations, interactions and activiti
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Figure 3. A comparison of knowledge
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ontology will easily be extensible
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Figure 7. Visual Representation of
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Step 5: Use Boolean to combine the
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2) CogSkillNet provides classroom i
Page 259 and 260: Neo, M., & Neo, T.-K. (2009). Engag
Page 261 and 262: • Conversation and collaboration
Page 263 and 264: IMAGE 2 2. Problem identification I
Page 265 and 266: Methodology At the end of the proje
Page 267 and 268: presentation skills (m = 3.72), and
Page 269 and 270: 6. Can’t be denying that, sometim
Page 271 and 272: Lambert, N. M., & McCombs, B. J. (1
Page 273 and 274: not detected in a previous study, t
Page 275 and 276: et al. (2001) studied the learning
Page 277 and 278: all the students. At the midpoint o
Page 279 and 280: The observed pairs were aware of be
Page 281 and 282: Table 2 shows the results from a mo
Page 283 and 284: Table 5: The distribution of time (
Page 285 and 286: As discussed in the section on prev
Page 287 and 288: McDowell, C., Werner, L., Bullock,
Page 289 and 290: Comprehension monitoring is the awa
Page 291 and 292: or roles in a context, such as “I
Page 293 and 294: Correlation coefficient was also co
Page 295 and 296: (a) Text 1 (b) Text 2 (c) Text 3 (d
Page 297 and 298: Table 3 shows that the average read
Page 299 and 300: Figure 10. Trace results of the les
Page 301 and 302: monitor their reading process and h
Page 303 and 304: Conn, S. R., Roberts, R. L., & Powe
Page 305 and 306: The technology-mediated groups, wit
Page 307 and 308: hybrid model of supervision was pos
Page 309: Our research indicates that the hyb
Page 313 and 314: goal of using storyboards. But, thi
Page 315 and 316: In general, learning activities nee
Page 317 and 318: Furthermore, free subjects, such as
Page 319 and 320: Storyboarding Roots and related wor
Page 321 and 322: Referees, on the other hand, may wa
Page 323 and 324: Symbols Interpretation Defines a un
Page 325 and 326: Figure 4. Top-level storyboard for
Page 327 and 328: may take subjects such as practical
Page 329 and 330: network security information envir
Page 331 and 332: The concrete procedure and interact
Page 333 and 334: (e.g., for graduation) using such i
Page 335 and 336: Thus, academic education modeling b
Page 337 and 338: Feyer, T., Kao, O., Schewe, K.-D.,
Page 339 and 340: Richards, G. (2009). Book review: T
Page 341 and 342: expands the child’s proximal envi
Page 343: Chapter 6 exemplifies the activitie
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