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Kenneth R. Koedinger

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Kenneth R. Koedinger

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Publications by Kenneth R. Koedinger (bibliography)

» 2008 «

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Bauer, Aaron and Koedinger, Kenneth R. (2008): Note-taking, selecting, and choice: designing interfaces that encourage smaller selections. In: JCDL08 Proceedings of the 8th ACM/IEEE-CS Joint Conference on Digital Libraries 2008. pp. 397-406. Available online

“Our research develops note-taking applications for educational environments. Previous studies found that while copy-pasting notes can be more efficient than typing, for some users it reduces attention and learning. This paper presents two studies aimed at designing and evaluating interfaces that encourage focusing. While we were able to produce interfaces that increased desirable behaviors and improved satisfaction, the new interfaces did not improve learning. We suggest design recommendations derived from these studies, and describe a "selecting-to-read" behavior we encountered, which has implications for the design of reading and note-taking applications.”

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» 2007 «

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Bauer, Aaron and Koedinger, Kenneth R. (2007): Selection-based note-taking applications. In: Proceedings of ACM CHI 2007 Conference on Human Factors in Computing Systems 2007. pp. 981-990. Available online

“The increasing integration of education and technology has led to the development of a range of note-taking applications. Our project's goal is to provide empirical data to guide the design of such note-taking applications by evaluating the behavioral and learning outcomes of different note-taking functionality. The study reported here compares note-taking using a text editor and four interaction techniques. The two standard techniques are typing and copy-paste. The two novel techniques are restricted copy-paste and menu-selection, intended to increase attention and processing respectively. Hypothesized learning gains from the novel techniques were not observed. As implemented these techniques were less efficient and appeared to be more frustrating to use. However, data regarding differences in both note-taking efficiency and learning suggest several important implications for selection-based note-taking applications, such as pasting and highlighting. Our results also indicate that students have strong opinions regarding their note-taking practices, which may complicate potentially beneficial interventions.”

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VanLehn, Kurt, Koedinger, Kenneth R., Skogsholm, Alida, Nwaigwe, Adaeze, Hausmann, Robert G. M., Weinstein, Anders and Billings, Benjamin (2007): What's in a Step? Toward General, Abstract Representations of Tutoring System Log Data. In: Conati, Cristina, McCoy, Kathleen F. and Paliouras, Georgios (eds.) User Modeling 2007 - 11th International Conference - UM 2007 June 25-29, 2007, Corfu, Greece. pp. 455-459. Available online

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Matsuda, Noboru, Cohen, William W., Sewall, Jonathan, Lacerda, Gustavo and Koedinger, Kenneth R. (2007): Evaluating a Simulated Student Using Real Students Data for Training and Testing. In: Conati, Cristina, McCoy, Kathleen F. and Paliouras, Georgios (eds.) User Modeling 2007 - 11th International Conference - UM 2007 June 25-29, 2007, Corfu, Greece. pp. 107-116. Available online

» 2006 «

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Bauer, Aaron and Koedinger, Kenneth R. (2006): Pasting and Encoding: Note-Taking in Online Courses. In: ICALT 2006 - Proceedings of the 6th IEEE International Conference on Advanced Learning Technologies 5-7 July, 2006, Kerkrade, The Netherlands. pp. 789-793. Available online

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Feng, Mingyu, Heffernan, Neil T. and Koedinger, Kenneth R. (2006): Addressing the testing challenge with a web-based e-assessment system that tutors as it assesses. In: Proceedings of the 2006 International Conference on the World Wide Web 2006. pp. 307-316. Available online

“Secondary teachers across the country are being asked to use formative assessment data to inform their classroom instruction. At the same time, critics of No Child Left Behind are calling the bill "No Child Left Untested" emphasizing the negative side of assessment, in that every hour spent assessing students is an hour lost from instruction. Or does it have to be? What if we better integrated assessment into the classroom, and we allowed students to learn during the test? Maybe we could even provide tutoring on the steps of solving problems. Our hypothesis is that we can achieve more accurate assessment by not only using data on whether students get test items right or wrong, but by also using data on the effort required for students to learn how to solve a test item. We provide evidence for this hypothesis using data collected with our E-ASSISTment system by more than 600 students over the course of the 2004-2005 school year. We also show that we can track student knowledge over time using modern longitudinal data analysis techniques. In a separate paper [9], we report on the ASSISTment system's architecture and scalability, while this paper is focused on how we can reliably assess student learning.”

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» 2005 «

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Anthony, Lisa, Yang, Jie and Koedinger, Kenneth R. (2005): Evaluation of multimodal input for entering mathematical equations on the computer. In: Proceedings of ACM CHI 2005 Conference on Human Factors in Computing Systems 2005. pp. 1184-1187. Available online

“Current standard interfaces for entering mathematical equations on computers are arguably limited and cumbersome. Mathematics notations have evolved to aid visual thinking and yet text-based interfaces relying on keyboard-and-mouse input do not take advantage of the natural two-dimensional aspects of math. Due to its similarities to paper-based mathematics, pen-based handwriting input may be faster, more efficient, and more preferable for entering mathematics on computers. This paper presents an empirical study that tests this hypothesis. We also explored a multimodal input method combining handwriting and speech because we hypothesize that it may enhance computer recognition and aid user cognition. Novice users were indeed faster, more efficient and enjoyed the handwriting modality more than a standard keyboard-and-mouse mathematics interface, especially as equation length and complexity increased. The multimodal handwriting-plus-speech method was faster and better liked than the keyboard-and-mouse method and was not much worse than handwriting alone.”

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Baker, Ryan Shaun, Corbett, Albert T., Koedinger, Kenneth R. and Roll, Ido (2005): Detecting When Students Game the System, Across Tutor Subjects and Classroom Cohorts. In: Ardissono, Liliana, Brna, Paul and Mitrovic, Antonija (eds.) User Modeling 2005 - 10th International Conference - UM 2005 July 24-29, 2005, Edinburgh, Scotland, UK. pp. 220-224. Available online

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Roll, Ido, Baker, Ryan Shaun, Aleven, Vincent, McLaren, Bruce M. and Koedinger, Kenneth R. (2005): Modeling Students' Metacognitive Errors in Two Intelligent Tutoring Systems. In: Ardissono, Liliana, Brna, Paul and Mitrovic, Antonija (eds.) User Modeling 2005 - 10th International Conference - UM 2005 July 24-29, 2005, Edinburgh, Scotland, UK. pp. 367-376. Available online

» 2004 «

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Baker, Ryan Shaun, Corbett, Albert T., Koedinger, Kenneth R. and Wagner, Annette (2004): Off-task behavior in the cognitive tutor classroom: when students "game the system. In: Dykstra-Erickson, Elizabeth and Tscheligi, Manfred (eds.) Proceedings of ACM CHI 2004 Conference on Human Factors in Computing Systems April 24-29, 2004, Vienna, Austria. pp. 383-390. Available online

“We investigate the prevalence and learning impact of different types of off-task behavior in classrooms where students are using intelligent tutoring software. We find that within the classrooms studied, no other type of off-task behavior is associated nearly so strongly with reduced learning as "gaming the system": behavior aimed at obtaining correct answers and advancing within the tutoring curriculum by systematically taking advantage of regularities in the software's feedback and help. A student's frequency of gaming the system correlates as strongly to post-test score as the student's prior domain knowledge and general academic achievement. Controlling for prior domain knowledge, students who frequently game the system score substantially lower on a post-test than students who never game the system. Analysis of students who choose to game the system suggests that learned helplessness or performance orientation might be better accounts for why students choose this behavior than lack of interest in the material. This analysis will inform the future re-design of tutors to respond appropriately when students game the system.”

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John, Bonnie E., Prevas, Konstantine, Salvucci, Dario D. and Koedinger, Kenneth R. (2004): Predictive human performance modeling made easy. In: Dykstra-Erickson, Elizabeth and Tscheligi, Manfred (eds.) Proceedings of ACM CHI 2004 Conference on Human Factors in Computing Systems April 24-29, 2004, Vienna, Austria. pp. 455-462. Available online

“Although engineering models of user behavior have enjoyed a rich history in HCI, they have yet to have a widespread impact due to the complexities of the modeling process. In this paper we describe a development system in which designers generate predictive cognitive models of user behavior simply by demonstrating tasks on HTML mock-ups of new interfaces. Keystroke-Level Models are produced automatically using new rules for placing mental operators, then implemented in the ACT-R cognitive architecture. They interact with the mock-up through integrated perceptual and motor modules, generating behavior that is automatically quantified and easily examined. Using a query-entry user interface as an example [19], we demonstrate that this new system enables more rapid development of predictive models, with more accurate results, than previously published models of these tasks.”

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» 2003 «

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Mitrovic, Antonija, Koedinger, Kenneth R. and Martin, Brent (2003): A Comparative Analysis of Cognitive Tutoring and Constraint-Based Modeling. In: Brusilovsky, Peter, Corbett, Albert T. and Rosis, Fiorella De (eds.) User Modeling 2003 - 9th International Conference - UM 2003 June 22-26, 2003, Johnstown, PA, USA. pp. 313-322. Available online

» 2002 «

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Aleven, Vincent and Koedinger, Kenneth R. (2002): An effective metacognitive strategy: learning by doing and explaining with a computer-based Cognitive Tutor. In Cognitive Science, 26 (2) pp. 147-179

» 2000 «

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Haverty, Lisa A., Koedinger, Kenneth R., Klahr, David and Alibali, Martha W. (2000): Solving inductive reasoning problems in mathematics: not-so-trivial pursuit. In Cognitive Science, 24 (2) pp. 249-298

» 1999 «

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Miller, Craig S., Lehman, Jill Fain and Koedinger, Kenneth R. (1999): Goals and learning in microworlds. In Cognitive Science, 23 (3) pp. 305-336

» 1990 «

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Koedinger, Kenneth R. and Anderson, John R. (1990): Abstract Planning and Perceptual Chunks: Elements of Expertise in Geometry. In Cognitive Science, 14 (4) pp. 511-550

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Changes to this page (author)

22 Feb 2010: Enabled abstracts to be shown on Kenneth R. Koedinger's author page.
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28 Apr 2003: Added the author to the bibliography

Publication statistics

Publication period:1990-2008
Publication count:16
Number of co-authors:32

Productive colleagues

Kenneth R. Koedinger's 3 most productive colleagues in number of publications:

Bonnie E. John:51
Jie Yang:33
John R. Anderson:28

Collaboration count

Number of publications with 3 favourite co-authors:

Aaron Bauer:3
Ryan Shaun Baker:3
Vincent Aleven:2

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Conference Calendar

Mar 22

Workshop on Pervasive healthcare in the home : Supporting patient motivation and engagement

Mar 22

UX People

Mar 22

ETRA '10 - Eye Tracking Research & Applications Symp.

Mar 21

“ Software design is the act of determining the user's experience with a piece of software. It has nothing to do with how the code works inside, or how big or small the code is. The designer's task is to specify completely and unambiguously the user's whole experience. ”

-- David Liddle, From Bringing Design to Software, edited by Terry Winograd, 1996 ”

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Kenneth R. Koedinger

Publications by Kenneth R. Koedinger (bibliography)

» 2008 «

» 2007 «

» 2006 «

» 2005 «

» 2004 «

» 2003 «

» 2002 «

» 2000 «

» 1999 «

» 1990 «

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