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Students may feel a barrier to share their writings with a tutor.They may also feel more comfortable with an automated reflective writing aid to self-disclose those private thoughts relevant for their reflection.Despite the importance of reflection for education, there is little research on artificial intelligence techniques to automate the analysis of writings regarding reflective thinking.
These writings are different as they are centered on the personal thought process and how to learn from individual experiences.
The writings are often very personal and can contain references to feelings. They may consider the perspectives of people who are important in their context or draw conclusions from contexts that are valued by the author.
There has been great success with the extensive research into automated text analysis methods for educational contexts (Dringus and Ellis ).
Despite these research successes showing the potential of automated text analysis for education, there has been not much research regarding the automated text analytics of reflection.
This research further investigates the potential of supervised machine learning algorithms to reliably annotate text segments of writings according to categories of a reflective writing model.
Researching automated methods to analyze reflection is important because the manual analysis poses constraints to teaching and research and may hamper deeply personal reflections.Reflective writings are different from the types of writings students normally perform, such as essays, literature surveys, or reports.Although reflective thinking may have gone into these writings, the reflective thought process is usually not expressed or developed in these writings as this is not their primary purpose.However, as discussed later in this work, some commonalities exist between the various theories of reflection.For the purpose of this paper, we define reflection as follows: Reflective thinking is a conscious, goal-oriented cognitive process that seeks to learn solutions to personally important, often weakly defined, ambiguous problems of past and present experience and anticipated future situations that often involve thinking about the important elements of the experience, a critical analysis of the problem including the analysis of the thinkers’ own personal perspective and feelings as well as the perspective of others in order to determine lessons-learned or future plans.).These findings enable reflection analytics that is immediate and scalable.) is an important educational practice recognized on national and international levels.The worldwide operating Organisation for Economic Co-operation and Development (OECD) has endorsed reflective thinking as important for a “successful life and well-functioning society” (Rychen and Salganik ).This study evaluates whether machine learning can be used to automate this manual analysis.The study investigates eight categories that are often used in models to assess reflective writing, and the evaluation is based on 76 student essays (5080 sentences) that are largely from third- and second-year health, business, and engineering students.Reflective writing is an important educational practice to train reflective thinking.Currently, researchers must manually analyze these writings, limiting practice and research because the analysis is time and resource consuming.