Teaching Multiple Concepts to Forgetful Learners

How can we help a forgetful learner learn multiple concepts within a limited time frame? While there have been extensive studies in designing optimal schedules for teaching a single concept given a learner's memory model, existing approaches for teaching multiple concepts are typically based on heuristic scheduling techniques without theoretical guarantees. In this paper, we look at the problem from the perspective of discrete optimization and introduce a novel algorithmic framework for teaching multiple concepts with strong performance guarantees. Our framework is both generic, allowing the design of teaching schedules for different memory models, and also interactive, allowing the teacher to adapt the schedule to the underlying forgetting mechanisms of the learner. Furthermore, for a well-known memory model, we are able to identify a regime of model parameters where our framework is guaranteed to achieve high performance. We perform extensive evaluations using simulations along with real user studies in two concrete applications: (i) an educational app for online vocabulary teaching; and (ii) an app for teaching novices how to recognize animal species from images. Our results demonstrate the effectiveness of our algorithm compared to popular heuristic approaches

Understanding Science Through Knowledge Organizers: An Introduction

We propose, in this paper, a teaching program based on a grammar of scientific language borrowed mostly from the area of knowledge representation in computer science and logic. The paper introduces an operationizable framework for understanding knowledge using knowledge representation (KR) methodology. We start with organizing concepts based on their cognitive function, followed by assigning valid and authentic semantic relations to the concepts. We propose that in science education, students can understand better if they organize their knowledge using the KR principles. The process, we claim, can help them to align their conceptual framework with that of experts which we assume is the goal of science education

Teaching Inverse Reinforcement Learners via Features and Demonstrations

Learning near-optimal behaviour from an expert's demonstrations typically relies on the assumption that the learner knows the features that the true reward function depends on. In this paper, we study the problem of learning from demonstrations in the setting where this is not the case, i.e., where there is a mismatch between the worldviews of the learner and the expert. We introduce a natural quantity, the teaching risk, which measures the potential suboptimality of policies that look optimal to the learner in this setting. We show that bounds on the teaching risk guarantee that the learner is able to find a near-optimal policy using standard algorithms based on inverse reinforcement learning. Based on these findings, we suggest a teaching scheme in which the expert can decrease the teaching risk by updating the learner's worldview, and thus ultimately enable her to find a near-optimal policy.Comment: NeurIPS'2018 (extended version

The Search for Invariance: Repeated Positive Testing Serves the Goals of Causal Learning

Positive testing is characteristic of exploratory behavior, yet it seems to be at odds with the aim of information seeking. After all, repeated demonstrations of one’s current hypothesis often produce the same evidence and fail to distinguish it from potential alternatives. Research on the development of scientific reasoning and adult rule learning have both documented and attempted to explain this behavior. The current chapter reviews this prior work and introduces a novel theoretical account—the Search for Invariance (SI) hypothesis—which suggests that producing multiple positive examples serves the goals of causal learning. This hypothesis draws on the interventionist framework of causal reasoning, which suggests that causal learners are concerned with the invariance of candidate hypotheses. In a probabilistic and interdependent causal world, our primary goal is to determine whether, and in what contexts, our causal hypotheses provide accurate foundations for inference and intervention—not to disconfirm their alternatives. By recognizing the central role of invariance in causal learning, the phenomenon of positive testing may be reinterpreted as a rational information-seeking strategy

Curriculum development for disadvantaged students enrolled in nursing courses in career and technical education programs

The purpose of this study was to identify the characteristics of special needs students in technical educational programs

Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners

In real-world applications of education, an effective teacher adaptively chooses the next example to teach based on the learner's current state. However, most existing work in algorithmic machine teaching focuses on the batch setting, where adaptivity plays no role. In this paper, we study the case of teaching consistent, version space learners in an interactive setting. At any time step, the teacher provides an example, the learner performs an update, and the teacher observes the learner's new state. We highlight that adaptivity does not speed up the teaching process when considering existing models of version space learners, such as "worst-case" (the learner picks the next hypothesis randomly from the version space) and "preference-based" (the learner picks hypothesis according to some global preference). Inspired by human teaching, we propose a new model where the learner picks hypotheses according to some local preference defined by the current hypothesis. We show that our model exhibits several desirable properties, e.g., adaptivity plays a key role, and the learner's transitions over hypotheses are smooth/interpretable. We develop efficient teaching algorithms and demonstrate our results via simulation and user studies.Comment: NeurIPS 2018 (extended version

Grammar & Writing: Pedagogy Behind Student Achievement

The purpose of this action research was to determine the effects of non-traditional teaching methods (not in isolation) with regards to the use of punctuation rules on student writing. The study took place in three Advanced English 9 classrooms with 78 students participating. Teaching strategies included the use of a web-based punctuation program, teacher-created and web-based instructional videos, teacher-created and web-based punctuation games, and the use of Google Docs via Google Classroom with both editing and conferencing. Data was collected through a student questionnaire, a student writing sample, a punctuation pre-test, two student writing assessments with error tally sheets via Google Docs, and a punctuation post-test. Data was also collected through teacher observations. The results indicated that the use of non-traditional teaching methods did not necessarily impact students’ use of punctuation rules on student writing. However, results did indicate that students were more engaged in the study of punctuation rules and were more aware of their writing skills and deficiencies at the conclusion of the study. Results also indicated that students were able to recognize incorrect use of punctuation in writing other than their own. The implication is that student writing with correct usage of punctuation rules needs to be continuous with constant practice and feedback

A CONTENT ANALYSIS ON ENGLISH TEXTBOOK OF “BAHASA DAN SASTRA INGGRIS X” USED BY STUDENTS OF MAN 1 SURAKARTA

ABSTRACT Febrian Giska Bangkit. 2017.A Content Analysis On English Textbook ”Bahasa dan Sastra Inggris X” Used by Students Of MAN 1 Surakarta. Thesis. English Education Department, Islamic Education and Teacher Training Faculty. Advisor : Dr. Imroatus Solikhah, M.Pd Key words : Content Analysis, Bahasa dan Sastra X English Textbook. The research is a content analysis on English textbook of “Bahasa dan Sastra Inggris X” used by students of MAN 1 Surakarta. The objectives of this research were to find out the quality of material English textbook for the tenth grade students of MAN 1 Surakarta. The researcher focuses on the quality of textbook suggested by checklist from Permendikbud (2016:8). The method used in this research was descriptive qualitative research. The subject of the research was the English textbook used by students of MAN 1 Surakarta. The instrument to collect the data is English textbook entitled “Bahasa dan Sastra Inggris X” for Senior High School published by Mediatama. The researcher analyzed the data by using descriptive qualitative research. The thrustwortiness of the reseach was methodological triangulation. From the result of the research, the researcher found the answer of the research problem that the textbook of "Bahasa dan Sastra Inggris X" that only two things which are not on the checklist from Permendikbud no 8. Tahun 2016. They are the higher retail price of the textbook and the image page on “Bahasa dan Sastra Inggris” textbook. So, “Bahasa dan Sastra Inggris” textbook are categorized in good textbook and suitable for X grade students according to checklist from Permendikbud No. 8 Tahun 2016

Interactive Teaching Algorithms for Inverse Reinforcement Learning

We study the problem of inverse reinforcement learning (IRL) with the added twist that the learner is assisted by a helpful teacher. More formally, we tackle the following algorithmic question: How could a teacher provide an informative sequence of demonstrations to an IRL learner to speed up the learning process? We present an interactive teaching framework where a teacher adaptively chooses the next demonstration based on learner's current policy. In particular, we design teaching algorithms for two concrete settings: an omniscient setting where a teacher has full knowledge about the learner's dynamics and a blackbox setting where the teacher has minimal knowledge. Then, we study a sequential variant of the popular MCE-IRL learner and prove convergence guarantees of our teaching algorithm in the omniscient setting. Extensive experiments with a car driving simulator environment show that the learning progress can be speeded up drastically as compared to an uninformative teacher.Comment: IJCAI'19 paper (extended version