COMP 6600 Assignment #4 By Delane Abigt due: Sept. 25, 2008

COMP 6600Assignment #4

By Delane Abigtdue: Sept. 25, 2008

SURL – Software Usability Research Lab at Wichita State University

SURL – Software Usability Research Lab An interesting project

• Eye Movement Patterns on Single and Dual-Column Web Pages

• This study examines eye movement patterns of users browsing or searching a 1-column and 2-column news article on a web page. The results show a higher number of fixations for information in the second column of an article than for the same information in the lower portion of a single column. In addition, the typical "F" pattern appeared in the left column of the 2-column layout, but not in the right column. Users also fixated more on other page elements, such as ads, when they were browsing than when they were searching.

• Our usability testing computer uses a 17” monitor integrated with the Tobii 1750 eye-tracking system, which can be used to detect and collect participant eye-gaze data during testing.

• The eye-tracker samples the position of the user’s eyes on an average of every 20ms (i.e., 50Hz) and is characterized by the unobtrusive addition of the eye-tracking hardware (e.g., high resolution camera and near infra-red light-emitting diodes) to the monitor frame. This design aspect helps promote more natural user behavior by not placing unnatural restrictions on participants (e.g., helmets, head-rests).

SURL – Software Usability Research Lab A Research Paper

• Does the Typeface of a Resume Impact Our Perception of the Applicant?

• by A. Dawn Shaikh & Doug Fox• Summary. Resumes play an important role when applying for a job.

Unfortunately, many applicants focus only on the content of the resume and not the physical appearance. The typeface chosen to display the resume not only influences the physical appearance, but also influences how an employer may view the applicant. In this study, resumes displayed in a high appropriate typeface (Corbel), resulted in the applicant being perceived as more knowledgeable, mature, experienced, professional, believable, and trustworthy than when displayed in a neutral typeface (Tempus Sans) or low appropriate typeface (Vivaldi). Moreover, the applicant was more likely to be called for an interview when their resume was displayed in a high appropriate typeface than a neutral or low appropriate typeface.

SURL – Software Usability Research Lab The Research Paper Citation

• Brumberger, E. R. (2001). The rhetoric of typography: Five experimental studies of typeface personality and its effects on readers and reading. Unpublished Dissertation, New Mexico State University, Las Cruces, NM.

• Creating a resume (2008, May 12). Retrieved May 20, 2008, from University of Wisconsin-Green Bay website: http://www.uwgb.edu/Careers/Creating_Resume.htm.

• Fletcher, L. (n.d.). Writing your first resume. Retrieved May 20, 2008, from About.com website: http://jobsearch.about.com/cs/resumewriting/a/firstresume.htm.

• Fox, D., Shaikh, A. D., & Chaparro, B. S. (2007). The effect of typeface appropriateness on the perception of documents. Proceedings of the Human Factors & Ergonomics Society 51st Annual Conference, USA, 51, 464-468.

• Kostelnick, C., & Hassett, M. (2003). Shaping information: The rhetoric of visual conventions. Carbondale, IL: Southern Illinois University Press.

• Kostelnick, C., & Roberts, D. D. (1998). Designing visual language: Strategies for professional communicators. Boston: Allyn and Bacon.

• Mackiewicz, J. (2004). What technical writing students should know about typeface personality. Journal of Technical Writing and Communication, 34, 113-131.

• Shaikh, A. D. (2007). Psychology of onscreen type: Investigation regarding typeface personality, appropriateness, and impact on document perception. Unpublished doctoral dissertation, Wichita State University.

• Thurstone, L. L. (1927a). A law of comparative judgment. Psychological Review, 34, 273-286. • Thurstone, L. L. (1927b). The method of paired comparisons for social values. Journal of Abnormal

and Social Psychology, 21(384-400). • Walker, P., Smith, S., & Livingston, A. (1986). Predicting the appropriateness of a typeface on the

basis of multi-modal features. Information Design Journal, 5, 29-42.

Accessibility Institute at the University of Texas at Austin

http://www.utexas.edu/disability/ai/about/lab.html

Accessibility Institute – Univ. of TX at Austin An interesting project - Participatory Design

• Accessibility Institute researchers used participatory design methods to obtain direct feedback from students and teachers about accessible computer technology. Accessibility Institute staff and teachers and 6th-9th grade students, with and without disabilities, designed prototypes of accessible Web sites. Students and teachers have definite technology preferences and expectations. These preferences are effectively integrated when users directly contribute to the design of their educational software.

• http://www.utexas.edu/disability/ai/research/summary/participatory.html

Accessibility Institute – Univ. of TX at Austin A Conference Proceeding Article

• CONVEYING CONTEXTUAL INFORMATION USING NON-SPEECH AUDIO CUES REDUCES WORKLOAD by Bronstad, P.M., Lewis, K., Slatin, J.

• The world wide web is rapidly becoming an indispensible resource, which holds great potential for people with visual impairments. Navigating html documents and getting information from them, however, is often very taxing for people who use screenreaders. People with visual impairments must listen to regular text and incorporated information about navigational and structural elements. All of this information must be properly interpreted in order to form a correct mental model of a document.

• For example, screenreaders often label hyperlinks by preceding them with the word "link," which can add to the difficulty of the task; the word is used to communicate something about the text that follows, although it could be interpreted as another word in a sentence, thereby increasing the complexity of the task.

• Researchers have investigated the effectiveness of aural elements such as "earcons" (Brewster, Wright, & Edwards, 1992) and other non-speech audio cues (Frankie, 1997). We investigated whether the use of non-speech audio cues can reduce cognitive workload to the extent that users can perform very complex tasks that they would otherwise find impossible.

• http://www.csun.edu/cod/conf/2003/proceedings/245.htm

Accessibility Institute – Univ. of TX at Austin The Conference Proceedings Articles References

• Brewster, S.A., Wright, P.C., & Edwards, A.D.N. (1992). A detailed investigation into the effectiveness of earcons. In G. Kramer (Ed.), Auditory display, sonification, audification and auditory interfaces. The Proceedings of the First International Conference on Auditory Display, Santa Fe Institute, Santa Fe, NM: Addison-Wesley, pp. 471-498.

• James, F. (1996). Presenting HTML Structure in Audio: User Satisfaction with Audio Hypertext. Proceedings of the International Conference on Auditory Display (ICAD), 97-103.

Microsoft Research New Englandhttp://research.microsoft.com/aboutmsr/labs/newengland/default.aspx

Microsoft Research New England

• Human-Computer Interaction Research on human-computer interaction (HCI) plays a central role across multiple teams at Microsoft Research. Our work is focused on advancing the way users interact with computing devices. This includes search, access, and information management, the display of complex data and information, user modeling and activity recognition, efficient input and interaction, the role of automation and the coupling of intelligent systems with direct manipulation.

http://research.microsoft.com/research/detail.aspx?id=2

Microsoft Research New England

• Social Computing We research and develop software that contributes to compelling and effective social interactions, with a focus on user-centered design processes and rapid prototyping. Our projects range from topics in online sharing and mobile applications to trust, reputation, and story telling. We’re interested in how people use computers to enhance their everyday experiences. We are designing interfaces and experiences to make human-to-human communication seamless and exciting.

http://research.microsoft.com/research/detail.aspx?id=6

Microsoft Research New England a Research Paper

• Reading Revisited: Evaluating the Usability of Digital Display Surfaces for Active Reading Tasks by Meredith Ringel Morris, A.J. Bernheim Brush, Brian R. Meyers

• A number of studies have shown that paper holds several advantages over computers for reading tasks. However, these studies were carried out several years ago, and since that time computerized reading tech-nology has advanced in many areas. We revisit the issue of reading in the workplace, comparing paper use to state-of-the-art hardware and software. In par-ticular, we studied how knowledge workers perform reading tasks in four conditions: (1) using paper, (2) using a dual-monitor desktop system, (3) using a pen-enabled horizontal display surface, and (4) using mul-tiple tablet computers. We discuss our findings, noting the strengths and shortcomings of each configuration. Based on these findings, we propose design guidelines for hybrid horizontal + vertical systems that support active reading tasks.

http://research.microsoft.com/~merrie/papers/reading.pdf

Microsoft Research New England The Research Paper Citation

• [1] Adler, A., Gujar, A., Harrison, B., O‟Hara, K., and Sel-len, A. A Diary Study of Work-Related Reading: De-sign Implications for Digital Reading Devices. Proc. of CHI 1998, 241-248.

• [2] Dietz, P. and Leigh, D. DiamondTouch: A Multi-User Touch Technology. Proc. of UIST 2001, 219-226. • [3] Dillon, A. Reading from Paper Versus Screens: A Criti-cal Review of the Empirical Literature. Ergonomics,

1992. • [4] Forlines, C. and Shen, C. DTLens: Multi-User Tabletop Spatial Data Exploration. Proc. of UIST 2005, 119-

122. • [5] Grudin, J. Partitioning Digital Worlds: Focal and Peri-pheral Awareness in Multiple Monitor Use. Proc. of

CHI 2001, 458-465. • [6] Guimbretière, F. Paper Augmented Digital Documents. Proc. of UIST 2003, 51-60. • [7] Harrison, S., Minneman, S., Back, M., Balsamo, A., Chow, M., Gold, R., Gorbet, M., and MacDonald, D.

The What of XFR: eXperiments in the Future of Read-ing. Interactions Magazine, 8(3), May/June 2001, 21-30.

• [8] Hornbaek, K. and Frokjaer, E. Reading of Electronic Documents: The Usability of Linear, Fisheye, and Overview + Detail Interfaces. Proc. of CHI 2001, 293-300.

• [9] Marshall, C. and Brush, A.J. Exploring the Relationship Between Personal and Public Annotations. Proc. of JCDL 2004, 349-357.

• [10] Marshall, C. and Ruotolo, C. Reading-in-the-Small: A Study of Reading on Small Form Factor Devices. Proc. of JCDL 2002, 56-64.

• [11] Morris, M.R., Huang, A., Paepcke, A., and Winograd, T. Cooperative Gestures: Multi-User Gestural Interac-tion for Co-located Groupware. Proc. of CHI 2006, 1201-1210.

• [12] Obendorf, H. Simplifying Annotation Support for Real-World Settings: A Comparative Study of Active Read-ing. Proc. of ACM Hyperteχt and Hypermedia 2003, 120-121.

• [13] O‟Hara, K. and Sellen, A. A Comparison of Reading Paper and On-Line Documents. Proc. of CHI 1997, 335-342.

Microsoft Research New England The Research Paper Citation (continued)

• [14] Piper, A.M., O‟Brien, E., Morris, M.R., and Winograd, T. SIDES: A Cooperative Tabletop Computer Game for Social Skills Development. Proc. of CSCW 2006, 1-10.

• [15] Schilit, B., Golovchinsky, G., and Price, M. Beyond Paper: Supporting Active Reading with Free Form Digi-tal Ink Annotations. Proc. of CHI 1998, 249-256.

• [16] Scott, S.D., Grant, K.D., and Mandryk, R.L. System Guidelines for Co-located, Collaborative Work on a Tabletop Display. Proc. of ECSCW 2003, 159-178.

• [17] Shen, C., Lesh, N., Forlines, C., and Vernier, F. Sharing and Building Digital Group Histories. Proc. of CSCW 2002, 324-333.

• [18] Shen, C., Everitt, K., and Ryall, K. UbiTable: Impromp-tu Face-to-Face Collaboration on Horizontal Interactive Surfaces. Proc. of UbiComp 2003, 281-288.

• [19] Shen, C., Vernier, F., Forlines, C., and Ringel, M. Di-amondSpin: An Extensible Toolkit for Around-the-Table Interaction. Proc. of CHI 2004, 167-174.

• [20] Sellen, A. and Harper, R. The Myth of the Paperless Office. The MIT Press, 2001. • [21] Tandler, P., Prante, T., Muller-Tomfelde, C., Streitz, N., and Steinmetz, R. ConnecTables: Dynamic

Coupling of Displays for the Flexible Creation of Shared Workspac-es. Proc. of UIST 2001, 11-19. • [22] Wellner, P. The DigitalDesk Calculator: Tangible Ma-nipulation on a Desk Top Display. Proc. of UIST

1991, 27-34. • [23] Wellner, P. Interacting with Paper on the DigitalDesk. Communications of the ACM, July 1993, 36(7),

87-96. • [24] Wigdor, D. and Balakrishnan, R. Empirical Investiga-tion into the Effect of Orientation on Text

Readability in Tabletop Displays. Proc. of ECSCW 2005, 205-224. • [25] Wilson, A. PlayAnywhere: A Compact Interactive Tab-letop Projection-Vision System. Proc. of UIST

2005, 83-92. • [26] Ziola, R., Kellar, M., and Inkpen, K. DeskJocky: Ex-ploiting Passive Surfaces to Display Peripheral

Informa-tion. Proc. of Interact 2007, in press.

URL – Texas Tech Universityhttp://www.english.ttu.edu/usability/default.asp

URL – Texas Tech University An Interesting Project - Certified User Experience Professional (CUEP) Training

• Introduction to the field through selected readings • Three-day workshop focusing on the methodologies and

practice of usability testing • Learn [more] about CUEP Training • This isn’t a lecture course. You will hit the ground running,

getting your hands on equipment from day one, hour one. We believe the best way to guarantee that you’ll be able to implement what you learn in the course is if you did it already in the course.

• The CUEP is truly the first course of its kind dedicated to providing intensive, hands-on training that focuses on practical concerns for those interested in learning how to be effective user experience professionals

URL – Texas Tech UniversityA Research Paper

• Introducing the Blank Page Technique by John R. Morris and Brian Still

• The objective of this research was to investigate the applicability of a new technique to the usability testing of wire frames. The use of wire-frame mockups can inhibit the conceptual contribution of users to the vertical design when dead links are included because traditional approaches have focused more on the content that is present, and less on the content that could be. The Blank Page Technique provides a way for users to remain involved in the conceptual elements of Web site design, even after programming has begun. The technique was evaluated during usability testing of a new Web site for prospective law students at the Texas Tech University School of Law. All five of the participants selected dead links while conducting tasks, after which they were provided with a blank piece of paper and a writing instrument. They then proceeded to record elements of content onto the pages, and on a couple of occasions, participants actually drew out the pages as they would expect them to appear. There were 12 occurrences of dead link selection, resulting in 52 items of user-suggested content. The results of this initial test of the Blank Page Technique are promising and demonstrate that there is potential for application in the user testing of wire frames.

• http://www.english.ttu.edu/usability/documents/BlankPages_012908.pdf

URL – Texas Tech UniversityThe Research Paper Citation

• Barnum, C. M. (2002). Usability Testing and Research. New York: Allyn and Bacon. • Boren, M.T., and Ramey, J. (2000). Thinking Aloud: Reconciling Theory and

Practice. IEEE Transactions of Professional Communication, 43(3), 261-278. • Grady, H.M., (2000). Web Site Design: A Case Study in Usability Testing Using

Paper Prototypes. Proceedings of 2000 Joint IEEE International and 18th Annual Conference on Computer Documentation (IPCC/SIGDOC 2000), 39-45.

• Molich, R., Ede, M.E., Kaasgaard, K., and Karyukin, B. (2004). Comparative usability evaluation. Behaviour & Information Technology, 23(1), 65-74.

• Nielsen, J. (1995). Using Paper Prototypes in Home-page Design. IEEE Software, 12(4), 88-89,97.

• Rettig, M. (1994). Prototyping for tiny fingers. Communications of the ACM, 37(4), 21-27.

• Rudd, J., Stern, K., and Isensee, S. (1996). Low vs. high-fidelity prototyping debate. Interactions, 3(1), 76-85.

• Sefelin, R., Tscheligi, M., Verena, G. (2003). Paper prototyping – what is it good for?: a comparison of paper- and computer-based low-fidelity prototyping. CHI ’03 extended abstracts on Human Factors in Computing Systems, 778-779.

HCII - Human Computer Interaction Institute at Carnegie Mellon

http://www.hcii.cs.cmu.edu/

HCII - Human Computer Interaction Institute An Interesting Project

Rapid Development of Cognitive Models and Tutors Cognitive Tutors have been successful in raising students' math test scores in high-school and middle-school classrooms, but their development requires considerable time and expertise. We are developing a set of authoring tools to make modeling both easier for experts and possible for novices in cognitive science. The tools draw on ideas of programming by demonstration, structured editing, and others. Careful application of HCI methods is key.

HCII - Human Computer Interaction Institute A Research Paper

Exploring the Assistance Dilemma in Experiments with Cognitive Tutors by Kenneth R. Koedinger and Vincent Aleven

Intelligent tutoring systems are highly interactive learning environments that have beenshown to improve upon typical classroom instruction. Cognitive Tutors are a type ofintelligent tutor based on cognitive psychology theory of problem solving and learning.Cognitive Tutors provide a rich problem-solving environment with tutorial guidance inthe form of step-by-step feedback, specific messages in response to common errors, andon-demand instructional hints. They also select problems based on individual studentperformance. The learning benefits of these forms of interactivity are supported, tovarying extents, by a growing number of results from experimental studies. As CognitiveTutors have matured and are being applied in new subject-matter areas, they have beenused as a research platform and, particularly, to explore interactive methods to supportmetacognition. We review experiments with Cognitive Tutors that have compareddifferent forms of interactivity and we reinterpret their results as partial answers to thegeneral question: How should learning environments balance information or assistancegiving and withholding to achieve optimal student learning? How best to achieve thisbalance remains a fundamental open problem in instructional science. We call thisproblem the “assistance dilemma” and emphasize the need for further science to yieldspecific conditions and parameters that indicate when and to what extent to useinformation giving versus information withholding forms of interaction.

http://act-r.psy.cmu.edu/papers/761/EPR-CognitiveTutors-distrib.pdf

HCII - Human Computer Interaction Institute The Research Paper Citation

• Aleven, V., & Koedinger, K.R. (2000a). Limitations of student control: Do students know when they need help? In G. Gauthier, C. Frasson, & K. VanLehn (Eds.), Proceedings of the 5th International Conference on Intelligent Tutoring Systems , ITS 2000, (pp. 292-303). Berlin: Springer Verlag.

• Aleven, V., & Koedinger, K. R. (2000b). The need for tutorial dialog to support selfexplanation. In C. P. Rose & R. Freedman (Eds.), Building Dialogue Systems for Tutorial Applications, Papers of the 2000 AAAI Fall Symposium (pp. 65-73). Technical Report FS-00-01. Menlo Park, CA: AAAI Press.

• Aleven, V., & Koedinger, K. R. (2002). An effective metacognitive strategy: Learning by doing and explaining with a computer-based Cognitive Tutor. Cognitive Science, 26(2).

• Aleven, V., McLaren, B., Roll, I., & Koedinger, K. (2006). Toward meta-cognitive tutoring: A model of help seeking with a Cognitive Tutor. International Journal of Artificial Intelligence and Education, 16, 101-128.

• Aleven, V., Stahl, E., Schworm, S., Fischer, F., & Wallace, R.M. (2003). Help seeking and help design in interactive learning environments. Review of Educational Research, 73(2), 277-320.

• Anderson, J. R. (1993). Rules of the mind. Hillsdale, N.J.: Erlbaum.• Anderson, J. R., Corbett, A. T., Koedinger, K. R., & Pelletier, R. (1995). Cognitive

tutors: Lessons learned. The Journal of the Learning Sciences, 4(2), 167-207.

HCII - Human Computer Interaction Institute The Research Paper Citation (continued)

• Anderson, J. R., Reder, L. M., & Simon, H. A. (1996). Situated learning and education. Educational Researcher, 25(4), 5-11.

• Anderson, J. R., Reder, L. M. & Simon, H. A. (1998). Radical constructivism and cognitive psychology. In D. Ravitch (Ed.) Brookings papers on education policy 1998. Washington, DC: Brookings Institute Press.

• Atkinson, R. K., Derry, S. J.; Renkl, A., & Wortham, D. (2000). Learning from examples: Instructional principles from the worked examples research. Review of Educational Research, 70(2) 181–214.

• Atkinson, R. K., Renkl, A., & Merrill, M. M. (2003). Transitioning from studying examples to solving problems: Effects of self-explanation prompts and fading worked-out steps. Journal of Educational Psychology, 95(4), 774-783.

• Baker, R. S., Corbett, A.T., Koedinger, K.R., & Wagner, A.Z. (2004). Off-task behavior in the Cognitive Tutor classroom: When students “game the system.” Proceedings of ACM CHI 2004: Computer-Human Interaction (pp. 383-390).

• Baker, R., Corbett, A., Koedinger, K. R., Evenson, S., Roll, I., Wagner, A., Naim, M., Raspat, J., Baker, D., & Beck, J. (2006). Adapting to when students game an intelligent tutoring system. In M. Ikeda, K. D. Ashley, & T.-W. Chan (Eds.), Proceedings of the 8th International Conference on Intelligent Tutoring Systems (pp. 392-401). Berlin: Springer-Verlag.

• Bloom, B.S. (1984). The 2-sigma problem: The search for methods of group instruction as effective as one-to-one tutoring. Educational Researcher, 13, 4-16.


• Clark, R. C., & Mayer, R. E. (2003). e-Learning and the Science of Instruction : Proven Guidelines for Consumers and Designers of Multimedia Learning. San Francisco: Jossey-Bass.

• Corbett, A. (2001). Cognitive computer tutors: solving the two-sigma problem. In M. Bauer, P. J. Gmytrasiewicz, & J. Vassileva (Eds.), Proceedings of the 2001 International Conference on User Modeling (pp. 137-147). Berlin: Springer Verlag.

• Corbett, A., & Anderson, J. R. (1995). Knowledge tracing: modeling the acquisition of procedural knowledge. User Modeling and User-Adapted Interaction, 4, 253-278.

• Chi, M. T. H., Bassok, M., Lewis, M. W., Reimann, P., & Glaser, R. (1989). Selfexplanations: How students study and use examples in learning to solve problems. Cognitive Science, 13(2), 145-182.

• Chi, M. T. H., de Leeuw, N., Chiu, M. H., & LaVancher, C. (1994). Eliciting selfexplanations improves understanding. Cognitive Science, 18(3), 439-477.

• Crowley R. S., & Medvedeva, O. (2006). An intelligent tutoring system for visual classification problem solving. Artificial Intelligence in Medicine, 36(1), 85-117.

• Crowley, R. S, Legowski E., Medvedeva O., & Tseytlin E. (2005). An ITS for medical classification problem-solving: Effects of tutoring and representations. In C. K. Looi,

• G. McCalla, B. Bredeweg, & J. Breuker (Eds.), Proceedings of the 12th International Conference on Artificial Intelligence (AIED 2005), Amsterdam, The Netherlands.


• Duch, B., Gron, S., & Allen, D. (2001). The Power of Problem-Based Learning; A Practical "How To" For Teaching Undergraduate Courses in Any Discipline. Stylus Publishing, LLC.

• Eberts, R. E. (1997). Computer-based instruction. In M. G. Helander, T. K. Landauer, & P. V. Prabhu (Eds), Handbook of Human-Computer Interaction (pp. 825-847). Amsterdam, The Netherlands: Elsevier Science B. V.

• Guskey, T. R. (1987). The essential elements of mastery learning. Journal of Classroom Interaction, 22(2), 19-22

• Kalyuga, S., Chandler, P., Tuovinen, J., & Sweller, J. (2001). When problem solving is superior to studying worked examples. Journal of Educational Psychology, 93(3), 579–588.

• Karjcik, J. & Starr, M. (2001). Learning science content in a project-based environment. In Tinker, R., & Krajcik, J. S. (Eds). Portable Technologies: Science Learning in Context. Netherlands: Kluwer Publishers.

• Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 1(2), 75–86.

• Kluger, A. N., & DeNisi, A. (1996). The effects of feedback intervention on performance: A historical review, a meta-analysis and a preliminary feedback intervention theory. Psychological Bulletin, 112(2), 254-284.


• Koedinger, K. R. (2002). Toward evidence for instructional design principles: Examples from Cognitive Tutor Math 6. In D. S. Mewborn, P. Sztajn, D. Y. White, H. G.

• Wiegel, R. L. Bryant, & K. Nooney (Eds.), Proceedings of twenty-fourth annual meeting of the North American Chapter of the International Group for the Psychology of Mathematics Education, Vol. 1, pp. 21-49. Columbus, OH: ERIC Clearinghouse for Science, Mathematics, and Environmental Education.

• Koedinger, K.R., & Anderson, J.R. (1993). Reifying implicit planning in geometry: Guidelines for model-based intelligent tutoring system design. In Lajoie, S., &Derry, S. (Eds.) Computers as Cognitive Tools. Hillsdale, NJ: Erlbaum.

• Koedinger, K. R., Anderson, J. R., Hadley, W. H., & Mark, M. A. (1997). Intelligent tutoring goes to school in the big city. International Journal of Artificial Intelligence in Education, 8, 30-43.

• Koedinger, K. R. & Corbett, A. T. (2006). Cognitive Tutors: Technology bringing learning science to the classroom. In K. Sawyer (Ed.), The Cambridge Handbook of the Learning Sciences. Cambridge University Press.

• Lepper, M. R., & Malone, T. W. (1987). Intrinsic motivation and instructional effectiveness in computer-based education. In R. E. Snow & M. J. Farr (Eds.), Aptitude, learning and instruction: Volume III Conative and affective process analyses. Hillsdale, NJ: Erlbaum.


• Lewis, M. W. (1989). Developing and evaluating the CMU Algebra Tutor: Tension between theoretically-driven and pragmatically-driven design. Paper presented at the annual meeting of the American Educational Research Association, San Francisco, CA.

• Mathan, S. A. (2003). Recasting the Feedback Debate: Benefits of Tutoring Error Detection and Correction Skills. Unpublished dissertation. Carnegie Mellon University.

• Mathan, S. A. & Koedinger, K. R. (2005) Fostering the Intelligent Novice: Learning from errors with metacognitive tutoring. Educational Psychologist. 40(4), 257-265.

• McLaren, B. M., Lim, S., Gagnon, F., Yaron, D., & Koedinger, K. R. (2006). Studying the effects of personalized language and worked examples in the context of a webbased intelligent tutor. In M. Ikeda, K. D. Ashley, & T.-W. Chan (Eds.), Proceedings of the 8th International Conference on Intelligent Tutoring Systems (pp. 318-328). Berlin: Springer-Verlag.

• McKendree, J. E. (1990). Effective feedback content for tutoring complex skills. Human Computer Interaction, 5, 381-414.

• Merrill, D. C., Reiser, B. J., Ranney, M., & Trafton, J. G. 1992. Effective tutoring techniques: Comparison of human tutors and intelligent tutoring systems. Journal of the Learning Sciences 2(3), 277-305.


• Morgan, P., & Ritter, S. (2002). An experimental study of the effects of Cognitive Tutor® Algebra I on student knowledge and attitude. (Available from Carnegie Learning, Inc., 1200 Penn Avenue, Suite 150, Pittsburgh, PA 15222). http://www.carnegielearning.com

• Nathan, M. J. (1998). Knowledge and situational feedback in a learning environment for algebra story problem solving. Interactive Learning Environments, 5, 135-159.

• Ohlsson, S. (1996). Learning from performance errors. Psychological Review, 103(2), 241-262.

• Ohlsson, S. & Mitrovic, A. (2006). Constraint-based knowledge representation for individualized instruction. Computer Science and Information Systems, 3(1), 1-22.

• Paas, F., & Van Merrienboer, J. (1994). Variability of worked examples and transfer of geometry problem-solving skills: A cognitive-load approach. Journal of Educational Psychology, 86, 122-133.

• Pavlik Jr., P. I. (in press). Timing is an order: Modeling order effects in the learning of information. In F. E. Ritter, J. Nerb, T. O'Shea & E. Lehtinen (Eds.), In order to learn: How the sequences of topics affect learning. New York, NY: Oxford University Press.

• Plano, G. S. (2004). The Effects of the Cognitive Tutor Algebra on student attitudes and achievement in a 9th grade Algebra course. Unpublished doctoral dissertation, Seton Hall University.


• Roll, I., Aleven, V., McLaren, B. M., Ryu, E., Baker, R., & Koedinger, K. R. (2006). The help tutor: Does metacognitive feedback improve students’ help-seeking actions, skills and learning? In M. Ikeda, K. D. Ashley, & T.-W. Chan (Eds.), Proceedings of the 8th International Conference on Intelligent Tutoring Systems (pp. 360-369). Berlin: Springer-Verlag.

• Renkl, A., Atkinson, R. K., & Große, C. S. (2004) How fading worked solution steps works - a cognitive load perspective. Instructional Science, 32, 59-82.

• Renkl, A. (2002). Learning from worked-out examples: Instructional explanations supplement self-explanations. Learning & Instruction, 12, 529-556.

• Renkl, A., Stark, R., Gruber, H., & Mandl, H. (1998). Learning from worked-out examples: the effects of example variability and elicited self-explanations. Contemporary Educational Psychology, 23, 90-108.

• Sarkis, H. (2004). Cognitive Tutor Algebra 1 program evaluation, Miami-Dade County Public Schools. The Reliability Group. (Available from Carnegie Learning, Inc., 1200 Penn Avenue, Suite 150, Pittsburgh, PA 15222)

• Schmidt, R.A. & Bjork, R.A. (1992). New conceptualizations of practice: common principles in three paradigms suggest new concepts for training. Psychological Science, 3 (4), 207-217

• Schoenfeld, A. (1983). Beyond the purely cognitive: Belief systems, social cognitions, and metacognitions as driving forces in intellectual performance. Cognitive Science, 7, 329-363.


• Schwartz, D. L., & Bransford, J. D. (1998). A time for telling. Cognition and Instruction, 16(4), 475- 522.

• Schwonke, R., Wittwer, J., Aleven, V., Salden, R., Krieg, C., & Renkl, A. (in press). Can tutored problem solving benefit from faded worked-out examples? In The Second European Cognitive Science Conference. Schworm, S. & Renkl, A. (2002). Learning by solved example problems: Instructional explanations reduce self-explanation activity. In W. D. Gray & C. D. Schunn (Eds.), Proceeding of the 24th Annual Conference of the Cognitive Science Society (pp.816-821). Mahwah, NJ: Erlbaum.

• Shneyderman , A. (2001). Evaluation of the Cognitive Tutor Algebra I program. Miami-Dade County Public Schools, Office Of Evaluation And Research. http://oer.dadeschools.net/algebra.pdf#search=%22Shneyderman%20miami%20cognitive%20tutor%22.

• Siegler, R. S. (2002). Microgenetic studies of self-explanation. In N. Garnott & J. Parziale (Eds.), Microdevelopment: A process-oriented perspective for studying development and learning (pp. 31-58). Cambridge, MA: Cambridge University Press.

• Slamecka, N. J., & Graf, P. (1978). The generation effect: Delineation of a phenomenon. Journal of Experimental Psychology: Human Learning and Memory, 4, 592-604.

• Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257-285.


• Sweller, J., & Cooper, G. A. (1985). The use of worked examples as a substitute for problem solving in learning algebra. Cognition and Instruction, 2, 59–89.

• Trafton, J. G., & Reiser, B.J. (1993). The contributions of studying examples and solving problems to skill acquisition. In M. Polson (Ed.), Proceedings of the Fifteenth annual conference of the Cognitive Science Society (1017-1022). Hillsdale, N.J.: Erlbaum.

• VanLehn, K. (2006). The behavior of tutoring systems. International Journal of Artificial Intelligence in Education, 16, 227-265.

• VanLehn, K., Jones, R. M., & Chi, M. T. H. (1992). A model of the self-explanation effect. The Journal of the Learning Sciences, 2, 1-59.

• Vygotsky, L. S. (1978). Mind in society. Cambridge, MA: Harvard University Press.• Ward, M., & Sweller, J. (1990). Structuring effective worked examples. Cognition

and Instruction, 7, 1-39.• White, B. Y. & Frederiksen, J. R. (1998). Inquiry, modeling, and metacognition:

Making science accessible to all students. Cognition and Instruction 16(1), 3-118.• Zhu, X., & Simon, H. A. (1987). Learning mathematics from examples and by doing.

Cognition and Instruction, 4(3), 137-166.