Formative computer-based feedback in the university classroom: Specific concept maps scaffold students' writing

Formative feedback can be regarded as a crucial scaffold for students' writing cohesive texts. However, especially in large lectures students rarely receive feedback on their writing product. Thus, computer-based feedback could be an alternative to provide formative feedback to students. However, it is less clear, how computer-based feedback should be designed to help students writing cohesive texts. For that purpose, we implemented three different computer-based feedback methods within an authentic large lecture class. We investigated effects of the format (outline versus concept map) and the specificity (specific versus general) of the feedback on students' perceived difficulty and the generation of cohesive texts. We found that specific concept map feedback was perceived as less difficult as compared to the general feedback or the specific outline feedback. Additionally, students who received specific feedback wrote explanatory texts that were more cohesive as compared to students with the general feedback. However, the format of the feedback (concept map versus outline) did not account for improvements of cohesion. Evidently, specific concept map feedback can be regarded as an efficient scaffold to provide cohesive explanations. Concept map feedback induced lowest levels of difficulty during revisions.Concept map feedback and outline feedback helped students improve text cohesion.Acceptance of feedback is crucial for students' revision implementations.

[1]  Yu-Min Wang,et al.  Determinants of firms' knowledge management system implementation: An empirical study , 2016, Comput. Hum. Behav..

[2]  Danielle S. McNamara,et al.  Learning from texts: Effects of prior knowledge and text coherence , 1996 .

[3]  N. S Moore,et al.  Student Use of Automated Essay Evaluation Technology during Revision , 2016 .

[4]  Michael Halliday,et al.  Cohesion in English , 1976 .

[5]  Joel Geske,et al.  Overcoming the Drawbacks of the Large Lecture Class , 1992 .

[6]  Stefanie Golke,et al.  The impact of elaborated feedback on text comprehension within a computer-based assessment , 2015 .

[7]  Michele H. Jackson,et al.  The learning environment in clicker classrooms: student processes of learning and involvement in large university‐level courses using student response systems , 2007 .

[8]  Kenneth S. Pope,et al.  Appendix A: American Psychological Association: Ethical Principles of Psychologists and Code of Conduct With the 2010 Amendments , 2013 .

[9]  S. Ainsworth DeFT: A Conceptual Framework for Considering Learning with Multiple Representations. , 2006 .

[10]  Dirk Ifenthaler,et al.  Students' Acceptance of Tablet PCs in the Classroom , 2016 .

[11]  James C. Lester,et al.  The Case for Social Agency in Computer-Based Teaching: Do Students Learn More Deeply When They Interact With Animated Pedagogical Agents? , 2001 .

[12]  Jan-Willem Strijbos,et al.  Inferring mindful cognitive-processing of peer-feedback via eye-tracking: role of feedback-characteristics, fixation-durations and transitions , 2015, J. Comput. Assist. Learn..

[13]  J. Hayes,et al.  Writing Research and the Writer. , 1986 .

[14]  V. Shute Focus on Formative Feedback , 2008 .

[15]  Eileen Kintsch,et al.  Summary Street: Interactive Computer Support for Writing , 2004 .

[16]  Peter van Rosmalen,et al.  Exploring formative feedback on textual assignments with the help of automatically created visual representations , 2012, J. Comput. Assist. Learn..

[17]  Rod D. Roscoe,et al.  Presentation, expectations, and experience: Sources of student perceptions of automated writing evaluation , 2017, Comput. Hum. Behav..

[18]  Danielle S. McNamara,et al.  Reversing the Reverse Cohesion Effect: Good Texts Can Be Better for Strategic, High-Knowledge Readers , 2007 .

[19]  Kirsten Berthold,et al.  The role of specificity, targeted learning activities, and prior knowledge for the effects of relevance instructions , 2014 .

[20]  Albert D. Ritzhaupt,et al.  On the utility of pictorial feedback in computer-based learning environments , 2015, Comput. Hum. Behav..

[21]  Herbert A. Simon,et al.  Why a Diagram is (Sometimes) Worth Ten Thousand Words , 1987 .

[22]  Matthias Nückles,et al.  Training the brain or tending a garden? Students’ metaphors of learning predict self-reported learning patterns , 2016 .

[23]  Jeanne R. Paratore,et al.  Local Coherence in Persuasive Writing: An Exploration of Chilean Students’ Metalinguistic Knowledge, Writing Process, and Writing Products , 2011 .

[24]  Jörg Wittwer,et al.  Reading Skill Moderates the Impact of Semantic Similarity and Causal Specificity on the Coherence of Explanations , 2014 .

[25]  E. Nussbaum,et al.  Promoting Argument-Counterargument Integration in Students' Writing , 2007 .

[26]  Elisa Carbone,et al.  Teaching Large Classes: Unpacking the Problem and Responding Creatively , 1998 .

[27]  Katherine E. Rowan,et al.  A Contemporary Theory of Explanatory Writing , 1988 .

[28]  Stephanie Herppich,et al.  Addressing knowledge deficits in tutoring and the role of teaching experience: Benefits for learning and summative assessment , 2014 .

[29]  Jan-Willem Strijbos,et al.  Peer feedback content and sender's competence level in academic writing revision tasks: Are they critical for feedback perceptions and efficiency? , 2010 .

[30]  Janis A. Cannon-Bowers,et al.  Feedback source modality effects on training outcomes in a serious game: Pedagogical agents make a difference , 2015, Comput. Hum. Behav..

[31]  Slava Kalyuga,et al.  Facilitating Flexible Problem Solving: A Cognitive Load Perspective , 2010 .

[32]  Robert D. van Valin,et al.  An Introduction to Syntax , 2001 .

[33]  Kwangsu Cho,et al.  Learning by reviewing , 2011 .

[34]  Rod D. Roscoe,et al.  Writing pal: Feasibility of an intelligent writing strategy tutor in the high school classroom , 2013 .

[35]  Jörg Wittwer,et al.  Why Instructional Explanations Often Do Not Work: A Framework for Understanding the Effectiveness of Instructional Explanations , 2008 .

[36]  Erin Marie Furtak,et al.  Exploring teachers' informal formative assessment practices and students' understanding in the context of scientific inquiry , 2007 .

[37]  Peggy A. Ertmer,et al.  Teacher beliefs and technology integration practices: A critical relationship , 2012, Comput. Educ..

[38]  A. Lachner,et al.  Bothered by abstractness or engaged by cohesion? Experts' explanations enhance novices' deep-learning. , 2015, Journal of experimental psychology. Applied.

[39]  Saskia Brand-Gruwel,et al.  Write between the lines: Electronic outlining and the organization of text ideas , 2012, Comput. Hum. Behav..

[40]  E. Stern,et al.  The Nature of Teachers' Pedagogical Content Beliefs Matters for Students' Achievement Gains: Quasi-Experimental Evidence from Elementary Mathematics. , 2002 .

[41]  Walt Detmar Meurers,et al.  Approximating Givenness in Content Assessment through Distributional Semantics , 2016, *SEM@ACL.

[42]  Matthias Nückles,et al.  Mind the Gap! Automated Concept Map Feedback Supports Students in Writing Cohesive Explanations , 2017, Journal of experimental psychology. Applied.

[43]  T. Anderson,et al.  Design-Based Research , 2012 .

[44]  Arthur C. Graesser,et al.  Coh-Metrix: Capturing Linguistic Features of Cohesion , 2010 .

[45]  M. Gleason,et al.  Better Communication in Large Courses , 1986 .

[46]  E. Deci,et al.  Handbook of Self-Determination Research , 2002 .

[47]  Helmut Schmid,et al.  Estimation of Conditional Probabilities With Decision Trees and an Application to Fine-Grained POS Tagging , 2008, COLING.

[48]  Matthew T. McCrudden,et al.  Relevance and Goal-Focusing in Text Processing , 2007 .

[49]  Larry H. Ludlow,et al.  Can Downsizing College Class Sizes Augment Student Outcomes?: An Investigation of the Effects of Class Size on Student Learning , 2010 .

[50]  Ibrahim Almarashdeh,et al.  Sharing instructors experience of learning management system: A technology perspective of user satisfaction in distance learning course , 2016, Comput. Hum. Behav..

[51]  Michael Cahill,et al.  Working Memory in Written Composition: An Evaluation of the 1996 Model , 2013 .

[52]  Joseph B. Cuseo The Empirical Case against Large Class Size: Adverse Effects on the Teaching, Learning, and Retention of First-Year Students. , 2007 .

[53]  Ulrike Cress,et al.  Knowledge Construction in Wikipedia: A Systemic-Constructivist Analysis , 2014 .

[54]  A. Renkl,et al.  Instructional Aids to Support a Conceptual Understanding of Multiple Representations. , 2009 .

[55]  Steve Graham,et al.  Formative Assessment and Writing , 2015, The Elementary School Journal.

[56]  Robert D. Abbott,et al.  Students' perceptions of large classes , 1987 .