Conversation-based assessment: A novel approach to boosting test-taking effort in digital formative assessment

[1]  Ulrich Ludewig,et al.  Effects of mode and medium in reading comprehension tests on cognitive load , 2023, Comput. Educ..

[2]  Carol M. Forsyth,et al.  Examining the Accuracy of a Conversation‐Based Assessment in Interpreting English Learners' Written Responses , 2021, ETS Research Report Series.

[3]  Jamie Costley,et al.  Digital storytelling with chatbots: mapping L2 participation and perception patterns , 2021, Interact. Technol. Smart Educ..

[4]  Sandra Katz,et al.  Linking Dialogue with Student Modelling to Create an Adaptive Tutoring System for Conceptual Physics , 2021, International Journal of Artificial Intelligence in Education.

[5]  Yu-Hung Chien,et al.  Development of an AI Userbot for Engineering Design Education Using an Intent and Flow Combined Framework , 2020, Applied Sciences.

[6]  Matthias Söllner,et al.  AI-Based Digital Assistants , 2019, Business & Information Systems Engineering.

[7]  James A. Landay,et al.  QuizBot: A Dialogue-based Adaptive Learning System for Factual Knowledge , 2019, CHI.

[8]  Steven L. Wise,et al.  The Effects of Effort Monitoring With Proctor Notification on Test-Taking Engagement, Test Performance, and Validity , 2019, Applied Measurement in Education.

[9]  Weijiao Huang,et al.  Designing and Evaluating Three Chatbot-Enhanced Activities for a Flipped Graduate Course , 2019, International Journal of Mechanical Engineering and Robotics Research.

[10]  G. T. Jackson,et al.  Evaluating English language learners’ conversations: Man vs. Machine , 2018, Computer Assisted Language Learning.

[11]  Raquel Oliveira Prates,et al.  Chatbots Explain Themselves: Designers' Strategies for Conveying Chatbot Features to Users , 2018, Journal on Interactive Systems.

[12]  J. Soland Are Achievement Gap Estimates Biased by Differential Student Test Effort? Putting an Important Policy Metric to the Test , 2018 .

[13]  J. Soland The Achievement Gap or the Engagement Gap?Investigating the Sensitivity of Gaps Estimates to Test Motivation , 2018, Applied Measurement in Education.

[14]  G. T. Jackson,et al.  Eliciting Deeper Evidence through Conversation-Based Assessments , 2018, Deep Comprehension.

[15]  Sandra Katz,et al.  A Comparison of Tutoring Strategies for Recovering from a Failed Attempt During Faded Support , 2018, AIED.

[16]  Robert O. Davis The impact of pedagogical agent gesturing in multimedia learning environments: A meta-analysis , 2018, Educational Research Review.

[17]  G. T. Jackson,et al.  Improving the Measurement of Cognitive Skills Through Automated Conversations , 2018 .

[18]  Theodore J. Christ,et al.  Progress Monitoring in Reading: Comparison of Weekly, Bimonthly, and Monthly Assessments for Students at Risk for Reading Difficulties in Grades 2–4 , 2018 .

[19]  G. T. Jackson,et al.  Conversation‐Based Assessment , 2016 .

[20]  Sandra Katz,et al.  Exploring Contingent Step Decomposition in a Tutorial Dialogue System , 2016, UMAP.

[21]  Barbara Di Eugenio,et al.  Shifting the Load: a Peer Dialogue Agent that Encourages its Human Collaborator to Contribute More to Problem Solving , 2017, International Journal of Artificial Intelligence in Education.

[22]  A. Graesser Conversations with AutoTutor Help Students Learn , 2016, International Journal of Artificial Intelligence in Education.

[23]  A. Conley,et al.  Raising the stakes: How students' motivation for mathematics associates with high- and low-stakes test achievement. , 2015, Learning and individual differences.

[24]  Juan-Diego Zapata-Rivera,et al.  Using Trialogues to Measure English Language Skills , 2015, J. Educ. Technol. Soc..

[25]  Vasile Rus,et al.  DeepTutor: An Effective, Online Intelligent Tutoring System That Promotes Deep Learning , 2015, AAAI.

[26]  Arthur C. Graesser,et al.  Learning by Communicating in Natural Language With Conversational Agents , 2014 .

[27]  Yen-Lin Chen,et al.  A courseware to script animated pedagogical agents in instructional material for elementary students in English education , 2014 .

[28]  Johanna D. Moore,et al.  BEETLE II: Deep Natural Language Understanding and Automatic Feedback Generation for Intelligent Tutoring in Basic Electricity and Electronics , 2014, International Journal of Artificial Intelligence in Education.

[29]  Amy E Barth,et al.  Predicting reading outcomes with progress monitoring slopes among middle grade students. , 2014, Learning and individual differences.

[30]  Maria Bertling,et al.  A CBAL™ SCIENCE MODEL OF COGNITION: DEVELOPING A COMPETENCY MODEL AND LEARNING PROGRESSIONS TO SUPPORT ASSESSMENT DEVELOPMENT , 2013 .

[31]  Arthur C. Graesser,et al.  Recent Advances in Conversational Intelligent Tutoring Systems , 2013, AI Mag..

[32]  Arthur C. Graesser,et al.  AutoTutor and affective autotutor: Learning by talking with cognitively and emotionally intelligent computers that talk back , 2012, TIIS.

[33]  Arthur C. Graesser,et al.  Improving the Efficiency of Dialogue in Tutoring. , 2012 .

[34]  Yan Piaw Chua,et al.  Effects of computer-based testing on test performance and testing motivation , 2012, Comput. Hum. Behav..

[35]  Tim Davey,et al.  Computer-Adaptive Testing for Students with Disabilities: A Review of the Literature. Research Report. ETS RR-11-32. , 2011 .

[36]  Diego Zapata-Rivera,et al.  Interlanguage pragmatics with a pedagogical agent: the request game , 2010 .

[37]  Carol L. Barry,et al.  Do Examinees Have Similar Test-Taking Effort? A High-Stakes Question for Low-Stakes Testing , 2010 .

[38]  Hong Wang,et al.  Comparability of Computerized Adaptive and Paper-Pencil Tests , 2010 .

[39]  Antonija Mitrovic,et al.  Towards Individualized Dialogue Support for Ill-Defined Domains , 2009, Int. J. Artif. Intell. Educ..

[40]  Victor Lavy,et al.  The Effects of High Stakes High School Achievement Awards: Evidence from a Randomized Trial , 2009 .

[41]  Arthur C. Graesser,et al.  ARIES: An Intelligent Tutoring System Assisted by Conversational Agents , 2009, AIED.

[42]  Arthur C. Graesser,et al.  MetaTutor: Analyzing Self-Regulated Learning in a Tutoring System for Biology , 2009, AIED.

[43]  Arthur C. Graesser,et al.  Agent Technologies Designed to Facilitate Interactive Knowledge Construction , 2008 .

[44]  Yigal Attali,et al.  EFFECT OF IMMEDIATE FEEDBACK AND REVISION ON PSYCHOMETRIC PROPERTIES OF OPEN‐ENDED GRE® SUBJECT TEST ITEMS , 2008 .

[45]  Michelene T. H. Chi,et al.  Observing Tutorial Dialogues Collaboratively: Insights About Human Tutoring Effectiveness From Vicarious Learning , 2008, Cogn. Sci..

[46]  Susan Bull,et al.  CALMsystem: A Conversational Agent for Learner Modelling , 2007, Knowl. Based Syst..

[47]  Hanna Eklöf,et al.  Skill and will: test‐taking motivation and assessment quality , 2010 .

[48]  Arthur C. Graesser,et al.  When Are Tutorial Dialogues More Effective Than Reading? , 2007, Cogn. Sci..

[49]  Hanna Eklöf,et al.  Development and Validation of Scores From an Instrument Measuring Student Test-Taking Motivation , 2006 .

[50]  Steven L. Wise,et al.  An Investigation of the Differential Effort Received by Items on a Low-Stakes Computer-Based Test , 2006 .

[51]  Arthur C. Graesser,et al.  AutoTutor: an intelligent tutoring system with mixed-initiative dialogue , 2005, IEEE Transactions on Education.

[52]  T. Haladyna,et al.  Construct-Irrelevant Variance in High-Stakes Testing. , 2005 .

[53]  J. D. Fletcher,et al.  Opportunities for New “Smart” Learning Environments Enabled by Next-Generation Web Capabilities , 2004 .

[54]  Scotty D. Craig,et al.  Affect and learning: An exploratory look into the role of affect in learning with AutoTutor , 2004 .

[55]  Vincent Aleven,et al.  Evaluating the Effectiveness of a Tutorial Dialogue System for Self-Explanation , 2004, Intelligent Tutoring Systems.

[56]  Heather H. Mitchell,et al.  AutoTutor: A tutor with dialogue in natural language , 2004, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.

[57]  Danielle S McNamara,et al.  iSTART: Interactive strategy training for active reading and thinking , 2004, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.

[58]  J. D. Fletcher,et al.  The Case for Advanced Distributed Learning , 2004 .

[59]  Albert T. Corbett,et al.  Cognitive Computer Tutors: Solving the Two-Sigma Problem , 2001, User Modeling.

[60]  Vincent Aleven,et al.  Towards Tutorial Dialog to Support Self- Explanation: Adding Natural Language Understanding to a Cognitive Tutor * , 2001 .

[61]  Arthur C. Graesser,et al.  AutoTutor: A simulation of a human tutor , 1999, Cognitive Systems Research.