Learning Scientific Concepts with Text Mining Support

This paper evaluates the use of a text mining tool to support learning of science concepts. The tool, called Sobek, extracts relevant information from unstructured data and represents it visually in a graph. Sobek was used here in an experiment with 36 students in 9th grade who had to learn concepts related to the particulate nature of matter. Students were divided in control (16) and experimental group (20). Students in the experimental group interacted with Sobek after reading a few texts, while the students in the control group carried out the activity in a more traditional way (reading/answering questions). Results from the experiment favored students in the experimental group, which led to the conclusion that Sobek did help students in the learning task.

[1]  Alberto J. Cañas,et al.  The Origins of the Concept Mapping Tool and the Continuing Evolution of the Tool* , 2006, Inf. Vis..

[2]  Diego Roman,et al.  Helping Students Bridge Inferences in Science Texts Using Graphic Organizers , 2016 .

[3]  Haluk Özmen,et al.  Determination of the Turkish primary students' views about the particulate nature of matter , 2007 .

[4]  Yuejin Xu,et al.  Using Text Mining Techniques to Analyze Students' Written Responses to a Teacher Leadership Dilemma , 2012 .

[5]  Haluk Özmen,et al.  Effect of animation enhanced conceptual change texts on 6th grade students' understanding of the particulate nature of matter and transformation during phase changes , 2011, Comput. Educ..

[6]  Breno Fabrício Terra Azevedo,et al.  Analysis of the Relevance of Posts in Asynchronous Discussions , 2014 .

[7]  Eliseo Reategui,et al.  Using Text-Mining to Support the Evaluation of Texts Produced Collaboratively , 2009, WCCE.

[8]  Mirjamaija Mikkilä-Erdmann,et al.  Improving Conceptual Change Concerning Photosynthesis through Text Design. , 2001 .

[9]  Robert J. Marzano,et al.  Visual Tools for Transforming Information Into Knowledge , 2008 .

[10]  Irene-Anna N. Diakidoy,et al.  Reading about energy: The effects of text structure in science learning and conceptual change , 2003 .

[11]  Ronen Feldman,et al.  Book Reviews: The Text Mining Handbook: Advanced Approaches to Analyzing Unstructured Data by Ronen Feldman and James Sanger , 2008, CL.

[12]  S. Vosniadou.  Capturing and modeling the process of conceptual change. , 1994 .

[13]  Kubilay Kaptan,et al.  Challenges for Science Education , 2012 .

[14]  Muhammad Kashif Hanif,et al.  Text Mining: Techniques, Applications and Issues , 2016 .

[15]  Mihaela Cocea,et al.  Text stream mining for Massive Open Online Courses: review and perspectives , 2014 .

[16]  Daniel Epstein,et al.  Automatic Extraction of Nonlinguistic Representations of Texts to Support Writing , 2015 .

[17]  Chong Ho Yu,et al.  Using Text Mining for Improving Student Experience Management in Higher Education , 2011 .

[18]  Carol L. Smith,et al.  Student Conceptions and Conceptual Change: Three Overlapping Phases of Research , 2014 .

[19]  Noah L. Schroeder,et al.  Studying and Constructing Concept Maps: a Meta-Analysis , 2018 .

[20]  Krys J. Kochut,et al.  A Brief Survey of Text Mining: Classification, Clustering and Extraction Techniques , 2017, ArXiv.

[21]  Russell Tytler,et al.  Picturing evaporation : learning science literacy through a particle representation , 2006 .

[22]  Barbara J. Guzzetti,et al.  Promoting conceptual change in science: A comparative meta-analysis of instructional interventions from reading education and science education , 1993 .