Semi-Automated Correction Tools for Mathematics-Based Exercises in MOOC Environments
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International Journal of Artificial Intelligence and Interactive Multimedia, Vol. 3, Nº 3 Semi-Automated Correction Tools for Mathematics-Based Exercises in MOOC Environments Alberto Corbí and Daniel Burgos Universidad Internacional de La Rioja the accuracy of the result but also in the correctness of the Abstract — Massive Open Online Courses (MOOCs) allow the resolution process, which might turn out to be as important as participation of hundreds of students who are interested in a –or sometimes even more important than– the final outcome wide range of areas. Given the huge attainable enrollment rate, it itself. Corrections performed by a human (a teacher/assistant) is almost impossible to suggest complex homework to students and have it carefully corrected and reviewed by a tutor or can also add value to the teacher’s view on how his/her assistant professor. In this paper, we present a software students learn and progress. The teacher’s feedback on a framework that aims at assisting teachers in MOOCs during correction sheet always entails a unique opportunity to correction tasks related to exercises in mathematics and topics improve the learner’s knowledge and build a more robust with some degree of mathematical content. In this spirit, our awareness on the matter they are currently working on. proposal might suit not only maths, but also physics and Exercises in physics deepen this reviewing philosophy and technical subjects. As a test experience, we apply it to 300+ physics homework bulletins from 80+ students. Results show our student-teacher interaction. Keeping an organized and solution can prove very useful in guiding assistant teachers coherent resolution flow is as relevant to the understanding of during correction shifts and is able to mitigate the time devoted the underlying physical phenomena as the final output itself. to this type of activities. Besides, in physics, results can belong to a broad spectrum of mathematical natures and entities, ranging from simple and Keyword s— assignments, semiautomated correction, maths, isolated numbers or scalars (e = 2.7182), vectors physics, framework. , signed quantities (-k) and physical units (3.3 kΩ), to name a few that might appear on a basic physics I. INTRODUCTION course. In addition, slightly different numbers, notations OOCs and online campuses nowadays represent an and/or symbols can represent exactly the same correct result M observable reality when it comes to self-education [5]. and account for the same reality. For instance, Together with OpenCourseWare platforms, they are definitively impacting our current TEL scene. Even in MOOC and can both be labeled as correct and the environments, students are usually required to carry out some student should receive a positive score/comment. If such homework. Nevertheless, these homework bulletins are hardly minor discrepancies could be detected, an automated system ever supervised by a tutor or a teacher. Quite the opposite, the might be able to send back an explicit recommendation as students themselves are required to self-correct and self-assess [26], for example, does. In the same sense, and as a last their exercises based on correction grids, templates and answer example, all of the following expressions have the exact same keys. Peer reviewing also takes place, as we will discuss in meaning: partial differentiation of function f with respect to an section II. Fully automated quizzes are also commonly independent variable x: displayed and correction is normally done by the MOOC and/or e-learning platform. Finally, students attending physics courses in online Technical documents from the STEM fields (Science, institutions and/or MOOCS come from very different Technology, Engineering and Mathematics) increase backgrounds and behavior is easily altered over time, as document richness with many sorts of structured objects: described by [1]. The human touch in the reviewing process mathematical and chemical formulae, diagrams, tables and has always proven to be the key to success, independently of relations, etc. These additions usually carry essential the academic environment: online, formal, higher education, information that complements the texts the student has to read. etc. At first sight, homework assignments related to these All this being said, in MOOC environments, the amount of disciplines are good candidates for automated correction homework bulletins to be reviewed, and the substantial processes. However, many teachers are interested not only in tutoring effort that takes place if every exercise from every -89- DOI: 10.9781/ijimai.2015.3312 Regular Issue student is manually revised, can reach disproportionate levels. detailed analysis of every learner, 1 by 1, and clustered by One of the goals of our project is concerned with assisting similarity. With A4Learning, the teacher can analyze the teachers during the correction phase. This target is achieved student current status, anticipate potential academic future, by pre-classifying student bulletins as ready to be teacher- and react in consequence. There is another early prototype, reviewed or not. In the latter case, an automated message can AppMOOC, which will retrieve basic requirements to grade be issued to the student, who can re-edit his/her own document activities, so that, when the professor gets an essay, a previous before reissuing it to the teacher, for a second time. Of course, checking mechanism guarantees that the work fulfills these this assistant tool would heavily depend on the type of subject minimum information and/or structure. These two prototypes, and content to be analyzed. In this paper, we focus on assisting A4Learning and AppMOOC, will be implemented along the teachers in online campuses and MOOCS when reviewing next academic year at a larger scale, with the clear objective of homework related to mathematical content. supporting teachers on their functions as evaluators and feedback providers, big mid-size and large-size groups of II. OVERVIEW OF THE CURRENT STATUS OF MOOCS, ONLINE learners, worldwide. The research work described in this paper EDUCATION AND STUDENT ASSIGNMENT MANAGEMENT is in intimate relation with the aforementioned projects. MOOCs face nowadays a number of challenges: accreditation management, credit recognition, monetization III. TOWARDS AN AUTOMATED HELPER SYSTEM FOR MATHS implementation and content and methodology quality AND TECHNICAL STUDENT HOMEWORK PRELIMINARY SCREENING assurance. Among them, methodology quality becomes the foundation from which the other four are built. MOOCs are We have designed a special workflow and protocol that taking over the long-tradition role of Open Educational automatically analyses student assignments and checks Resources. Some MOOCs also combine face-to-face strategies whether they contain coherent mathematical information with online learning and even merge formal and informal related to specific fields. This set of tools also takes into settings. In addition, MOOCs highlight the current need for account equivalent expressions, exemplified in section I. basic and specific competence acquisition, as a complement to In order to check for this coherence, simple –but also highly the current courses, very much focused on personal interests configurable and easily editable– content-checking rules and continuing education. They are also turning out the designed by the teacher are submitted to the correction engine. ultimate tool to fight against the lack of access to teaching Then, for every exercise in the student digital notebook, resources (disadvantaged individuals, regions and countries). mathematical expressions are semantically compared with the MOOC platforms require support for teachers and tutors, correction template submitted by the teacher. A more detailed based on their needs, skills, and teaching context. One of these review of the practical implementation is tackled below. has to do with grading essays and activities. Since MOOCs Of course, designing such a protocol is no easy task and has seeks the enrollment of hundreds or thousands of students, the required working with state-of-the-art mathematical language- evaluation becomes a real challenge. At present, some processing techniques and mathematics representation MOOCs rely on peer-assessment and counseling. Peer-to-peer standards, also reviewed below. seems significant and useful, so there is, at first sight, no need A. State-of-the-Art Language Processing in Mathematics for a replacement. However, a complementary evaluation resource would be welcome by the educational community. Despite the fact that linguistic analysis of scientific There are some approaches for automatic or semi-automatic documents is currently seen as an interesting line of research, assessment, like ontology networks [23], where the the current work in the field is still limited. Mathematical conceptualization of the domain model becomes the literature represents a rather isolated linguistic niche cornerstone to categorize and shapes the results properly. embodying its own challenges. We can identify a significant Another strategy involves the temporal hiring of additional contrast between this linguistic realm and, for instance, the teachers as graders, so they can act as complement to those domain of medical/healthcare research publications that have professors officially assigned to the course. In addition, a been studied by many scientific groups in recent years. Two of detailed comment and assessment on the submitted final the