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25
What Makes a Great MOOC? An Interdisciplinary Analysis of Student Retention in Online Courses
- In Proceedings of the 34th International Conference on Information Systems, ICIS ’13
, 2013
"... Massive Open Online Courses (MOOCs) have experienced rapid expansion and gained significant popularity among students and educators. Although the broad acceptance of MOOCs, there is still a long way to go in terms of satisfaction of students ’ needs, as witnessed in the extremely high drop-out rates ..."
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Cited by 18 (6 self)
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Massive Open Online Courses (MOOCs) have experienced rapid expansion and gained significant popularity among students and educators. Although the broad acceptance of MOOCs, there is still a long way to go in terms of satisfaction of students ’ needs, as witnessed in the extremely high drop-out rates. Working toward improving MOOCs, we employ the Grounded Theory Method (GTM) in a quantitative study and explore this new phenomenon. In particular, we present a novel analysis using a real-world data set with user-generated online reviews, where we both identify the student, course, platform, and university characteristics that affect student retention and estimate their relative effect. In the conducted analysis, we integrate econometric, text mining, opinion mining, and machine learning techniques, building both explanatory and predictive models, toward a more complete analysis. This study also provides actionable insights for MOOCs and education, in general, and contributes to the related literature discovering new findings.
Automatically generating problems and solutions for natural deduction
- In IJCAI
, 2013
"... Natural deduction, which is a method for establishing validity of propositional type arguments, helps develop important reasoning skills and is thus a key ingredient in a course on introductory logic. We present two core components, namely solution generation and practice problem generation, for ena ..."
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Cited by 8 (4 self)
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Natural deduction, which is a method for establishing validity of propositional type arguments, helps develop important reasoning skills and is thus a key ingredient in a course on introductory logic. We present two core components, namely solution generation and practice problem generation, for enabling computer-aided education for this important subject domain. The key enabling technology is use of an offline-computed data-structure called Universal Proof Graph (UPG) that encodes all possible applications of inference rules over all small propositions abstracted using their bitvector-based truth-table representation. This allows an efficient forward search for solution generation. More interestingly, this allows generating fresh practice problems that have given solution characteristics by performing a backward search in UPG. We obtained around 300 natural deduction problems from various textbooks. Our solution generation procedure can solve many more problems than the traditional forward-chaining based procedure, while our problem generation procedure can efficiently generate several variants with desired characteristics. 1
Automated Grading of DFA Constructions
, 2013
"... One challenge in making online education more effective is to develop automatic grading software that can provide meaningful feedback. This paper provides a solution to automatic grading of the standard computation-theory problem that asks a student to construct a deterministic finite automaton (DFA ..."
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Cited by 8 (4 self)
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One challenge in making online education more effective is to develop automatic grading software that can provide meaningful feedback. This paper provides a solution to automatic grading of the standard computation-theory problem that asks a student to construct a deterministic finite automaton (DFA) from the given description of its language. We focus on how to assign partial grades for incorrect answers. Each student’s answer is compared to the correct DFA using a hybrid of three techniques devised to capture different classes of errors. First, in an attempt to catch syntactic mistakes, we compute the edit distance between the two DFA descriptions. Second, we consider the entropy of the symmetric difference of the languages of the two DFAs, and compute a score that estimates the fraction of the number of strings on which the student answer is wrong. Our third technique is aimed at capturing mistakes in reading of the problem description. For this purpose, we consider a description language MOSEL, which adds syntactic sugar to the classical Monadic Second Order Logic, and allows defining regular languages in a concise and natural way. We provide algorithms, along with optimizations, for transforming MOSEL descriptions into DFAs and vice-versa. These allow us to compute the syntactic edit distance of the incorrect answer from the correct one in terms of their logical representations. We report an experimental study that evaluates hundreds of answers submitted by (real) students by comparing grades/feedback computed by our tool with human graders. Our conclusion is that the tool is able to assign partial grades in a meaningful way, and should be preferred over the human graders for both scalability and consistency.
Educational Software Engineering: Where Software Engineering, Education, and Gaming Meet
"... Abstract—We define and advocate the subfield of educational software engineering (i.e., software engineering for education), which develops software engineering technologies (e.g., software testing and analysis, software analytics) for general educational tasks, going beyond educational tasks for so ..."
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Cited by 8 (7 self)
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Abstract—We define and advocate the subfield of educational software engineering (i.e., software engineering for education), which develops software engineering technologies (e.g., software testing and analysis, software analytics) for general educational tasks, going beyond educational tasks for software engineering. In this subfield, gaming technologies often play an important role together with software engineering technologies. We expect that researchers in educational software engineering would be among key players in the education domain and in the coming age of Massive Open Online Courses (MOOCs). Educational software engineering can and will contribute significant solutions to address various critical challenges in education especially MOOCs such as automatic grading, intelligent tutoring, problem generation, and plagiarism detection. In this position paper, we define educational software engineering and illustrate Pex for Fun (in short as Pex4Fun), one of our recent examples
Autonomously generating hints by inferring problem solving policies
- In Proceedings of the Second (2015) ACM Conference on Learning@ Scale, L@S ’15
, 2015
"... Exploring the whole sequence of steps a student takes to pro-duce work, and the patterns that emerge from thousands of such sequences is fertile ground for a richer understanding of learning. In this paper we autonomously generate hints for the Code.org ‘Hour of Code, ’ (which is to the best of our ..."
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Cited by 7 (3 self)
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Exploring the whole sequence of steps a student takes to pro-duce work, and the patterns that emerge from thousands of such sequences is fertile ground for a richer understanding of learning. In this paper we autonomously generate hints for the Code.org ‘Hour of Code, ’ (which is to the best of our knowledge the largest online course to date) using historical student data. We first develop a family of algorithms that can predict the way an expert teacher would encourage a student to make forward progress. Such predictions can form the ba-sis for effective hint generation systems. The algorithms are more accurate than current state-of-the-art methods at recreat-ing expert suggestions, are easy to implement and scale well. We then show that the same framework which motivated the hint generating algorithms suggests a sequence-based statis-tic that can be measured for each learner. We discover that this statistic is highly predictive of a student’s future success.
Toward facilitating assistance to students attempting engineering design problems
- In Proceedings of the Tenth Annual International Conference on International Computing Education Research, ICER ’13
, 2013
"... In engineering design courses, many problems have a specification that the student’s implementation must meet, but give the student a large range of freedom for the internal design of that implementation. There may be several distinct, correct strategies for solving them, some of which may be unknow ..."
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Cited by 5 (3 self)
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In engineering design courses, many problems have a specification that the student’s implementation must meet, but give the student a large range of freedom for the internal design of that implementation. There may be several distinct, correct strategies for solving them, some of which may be unknown to the teaching staff or intelligent tutor designer. When a student is pursuing an unrecognized strategy and begins to struggle, staff may redirect them, costing unnecessary work, and automated hint generators may offer unhelpful feedback. We have taken a first step toward discovering these alternate correct strategies by visualizing many student solutions together, using dynamic and static features of these solutions, so that the teaching staff can understand the space of correct strategies. This approach has been applied to two domains: an online Matlab programming challenge and an undergraduate computer architecture course. We discuss these initial investigations and pose discussion questions to the community about potential enhancement and application of this analysis.
Virtualizing Cyber-Physical Systems: Bringing CPS to Online Education
"... Abstract—The advent of the massive open online course promises to bring world-class education to anyone with internet access. Instructors use blended models of education to deliver course content via video, text, interactive assignments, exams, wikis, and discussion forums. Courses with largely theo ..."
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Cited by 3 (1 self)
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Abstract—The advent of the massive open online course promises to bring world-class education to anyone with internet access. Instructors use blended models of education to deliver course content via video, text, interactive assignments, exams, wikis, and discussion forums. Courses with largely theoretical content are readily adapted to blended models for online audiences, but significant challenges arise when incorporating projectbased learning and interactive experiments. Cyber-physical systems courses commonly include experiments that explore the interplay between computation and physics and are especially subject to the challenges of bringing experimentation and projectbased learning to online audiences. We describe technical aspects of embedded and cyber-physical systems laboratory exercises used at the University of California, Berkeley, and investigate avenues for adapting this content to a massive open online course. I.
Programming by demonstration framework applied to procedural math problems
, 2013
"... K-12 mathematics includes many procedures to be learned, such as addition and subtraction, and there are many “buggy ” or incor-rect procedures that students demonstrate during this learning pro-cess. Learning such procedures (both correct and incorrect) from demonstration traces has various applica ..."
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Cited by 2 (2 self)
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K-12 mathematics includes many procedures to be learned, such as addition and subtraction, and there are many “buggy ” or incor-rect procedures that students demonstrate during this learning pro-cess. Learning such procedures (both correct and incorrect) from demonstration traces has various applications in computer-aided education. We formalize mathematical procedures as spreadsheet programs, involving loops and conditionals over a given set of base operators, and present a novel algorithm for synthesizing such pro-cedures from demonstrations. Our algorithm is based on dynamic programming and leverages ideas from version-space algebras and template-based program synthesis. Our implementation efficiently synthesized programs to solve 20 common math procedures and re-produce 28 different kinds of bugs that were demonstrated by real students across 9 procedures. Our implementation significantly out-performs SKETCH, a state of the art program synthesizer, on these tasks. We also demonstrate the applicability of our generic program synthesis technology to spreadsheet table transformations, an im-portant domain in end-user programming. 1.
Cost-aware automatic program repair
- SAS, volume 8723 of LNCS
, 2014
"... Abstract. We present a formal framework for repairing infinite-state, imperative, sequential programs, with (possibly recursive) procedures and multiple assertions; the framework can generate repaired programs by modifying the original erroneous program in multiple program lo-cations, and can ensure ..."
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Cited by 2 (0 self)
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Abstract. We present a formal framework for repairing infinite-state, imperative, sequential programs, with (possibly recursive) procedures and multiple assertions; the framework can generate repaired programs by modifying the original erroneous program in multiple program lo-cations, and can ensure the readability of the repaired program using user-defined expression templates; the framework also generates a set of inductive assertions that serve as a proof of correctness of the repaired program. As a step toward integrating programmer intent and intuition in automated program repair, we present a cost-aware formulation — given a cost function associated with permissible statement modifica-tions, the goal is to ensure that the total program modification cost does not exceed a given repair budget. As part of our predicate abstraction-based solution framework, we present a sound and complete algorithm for repair of Boolean programs. We have developed a prototype tool based on SMT solving and used it successfully to repair diverse errors in benchmark C programs. 1
OverCode: Visualizing Variation in Student Solutions to Programming Problems at Scale 7:35
- In Proceedings of the 10th Annual International ACM Conference on International Computing Education Research (ICER’13).
, 2013
"... In MOOCs, a single programming exercise may produce thousands of solutions from learners. Understanding solution variation is important for providing appropriate feedback to students at scale. The wide variation among these solutions can be a source of pedagogically valuable examples and can be use ..."
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Cited by 2 (2 self)
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In MOOCs, a single programming exercise may produce thousands of solutions from learners. Understanding solution variation is important for providing appropriate feedback to students at scale. The wide variation among these solutions can be a source of pedagogically valuable examples and can be used to refine the autograder for the exercise by exposing corner cases. We present OverCode, a system for visualizing and exploring thousands of programming solutions. OverCode uses both static and dynamic analysis to cluster similar solutions, and lets teachers further filter and cluster solutions based on different criteria. We evaluated OverCode against a nonclustering baseline in a within-subjects study with 24 teaching assistants and found that the OverCode interface allows teachers to more quickly develop a high-level view of students' understanding and misconceptions, and to provide feedback that is relevant to more students' solutions.
