Let's start sewing

Master's Project (M.A.) University of Alaska Fairbanks, 2016This paper proposes Task Based Language Teaching (TBLT) as a teaching method for Ahtna language learners. TBLT focuses on engaging learners in meaningful activities or tasks which they accomplish through using the target language, learning Ahtna in the process. TBLT incorporates deeper understandings and meaning by teaching students the language in a cultural context. For this paper, the focus activity will be making a beaded necklace. Beading has been an important activity for me, from the time of learning about my culture and people from my Aunt Katie Wade. The website accompanying the project and be found at: http://www.ourlanguagecameback.com/

Grammatical errors in spoken english of University students in oral communication course

The present study examines the grammatical errors in spoken English of university students who are less proficient in English. The specific objectives of the study are to determine the types of errors and the changes in grammatical accuracy during the duration of the English for Social Purposes course focussing on oral communication. The language data were obtained from the simulated oral interactions of 42 students participating in five role play situations during the 14-week semester. Error analysis of 126 oral interactions showed that the five common grammar errors made by the learners are preposition, question, article, plural form of nouns, subject-verb agreement and tense. Based on Dulay, Burt and Krashen’s (1982) surface structure taxonomy, the main ways by which students modify the target forms are misinformation and omission, with addition of elements or misordering being less frequent. The results also showed an increase in grammatical accuracy in the students’ spoken English towards the end of the course

Modeling the perceptual component of conceptual learning—A coordination perspective

Although a picture may be worth a thousand words, modeling diagrams as propositions and modeling visual processing as search through a database of verbal descriptions obscures what is problematic for the learner. Cognitive modeling of language learning and geometry has obscured the learner's problem of knowing where to look—what spaces, markings, and orientations constitute the objects of interest? Today we are launching into widespread use of multimedia instructional technology, without an adequate theory to relate perceptual processes to conceptual learning. Does this matter? In this article, I review the symbolic approach to modeling perceptual processing and show its limitations for explaining difficulties children encounter in interpreting a graphic display. I present an alternative analysis by which perceptual categorization is coupled to behavior sequences, where gesturing and emotional changes are essential for resolving impasses and breaking out of loops. I conclude by asking what kind of cognitive theory we need to exploit communication technology. Have we been correct to assume that pedagogy must be grounded in an accurate psychological model of knowledge, memory, and learning

Research on the Innovation of English Teaching Mode Based on Artificial Intelligence

This article presents a research on innovative approaches in English language teaching through the application of Artificial Intelligence (AI). The aim is to address the issues found in traditional English language teaching methods by utilizing AI technology. The article begins by identifying the problems in traditional English language teaching and exploring the current applications of AI in education. Then, it specifically discusses the application of AI technology in English language teaching, such as interactive listening training, intelligent error correction and personalized post-class guidance, and cloud-based intelligent English translation teaching. Subsequently, a proposal is put forward to construct a new English language teaching system based on AI technology, including modules for engaging explanations, interactive English assignments, and creating scenarios for cross-cultural communication oral training. Lastly, an evaluation method for assessing the innovation of English language teaching models based on AI is introduced, which includes feedback and perceptions from both teachers and students, as well as an assessment of teaching outcomes. The research findings of this article can provide a more intelligent, personalized, and effective English language teaching approach, thus positively impacting the quality of English language teaching and enhancing students’ interest in learning

Integrating form and meaning in L2 pronunciation instruction

One of the central challenges of ESL teaching is striking the right balance between form and meaning. In pronunciation pedagogy, this challenge is compounded because repetitive practice, which has been shown to enhance phonological acquisition and promote fluency, is widely viewed as being incompatible with communicative principles. This article provides a brief historical background for modern pronunciation pedagogy (from World War II to the present) as part of a backdrop for understanding the current disjuncture between pronunciation and communicative language teaching. A discussion on form-focused instruction, its applicability for pronunciation pedagogy, and challenges in implementation follows with reference to a recent article that presents evidence for the appropriateness of a communicative instructional framework for teaching L2 pronunciation (Trofimovich & Gatbonton, 2006). Finally, a communicative activity that encourages repetitive practice while integrating pronunciation with other components of language use is proposed

“MacGyver-Meets-Dr. Ruth”: Science Journalism and the Material Positioning of Dr. Carla Pugh

This article examines the rhetorical consequences of foregrounding female scientists\u27 materials through an analysis of seven news articles on Dr. Carla Pugh, a surgeon who designs medical patient simulators. Journalists foreground Pugh\u27s materials by positioning her as both “MacGyver,” creatively assembling simulators from everyday objects, and “Dr. Ruth,” willingly discussing intimate parts. These positions avoid focusing on Pugh\u27s personal life or body but still ultimately gender her and her work. The MacGyver position associates Pugh with gendered activities, objects, and spaces while undermining her affiliation with the technical aspects of design. Meanwhile, the Dr. Ruth position implies Pugh\u27s knowledge comes from inherent bodily expertise, making certain scientific fields appear more natural for women

The role of machine learning in personalised instructional sequencing for language learning

The origins of personalised instructional sequencing can be dated back to the times of the Ancient Greeks to the times of Alexander The Great's tutor, Aristotle. However, over the centuries the demand for education and growth of students has been disproportionately greater than the number of teachers in training. Therefore, there has been a longstanding interest in finding a way to scale education without negatively affecting learning outcomes. This interest was fuelled further with the advent of computers and artificial intelligence, where a plethora of systems and models were built to bring technology driven personalised instructional sequencing to the world. Unfortunately, results were far from groundbreaking and many challenges still remain. In my thesis, I investigate three aspects of personalised instructional sequencing: the personalised instructional sequencing mechanism, the student knowledge representation, and human forgetting. While I do not cover the entirety of personalised instructional sequencing, I cover what I consider the foundational components. I link psychological theory to model selection and design in each of my systems and present experiments to illustrate their impact. I show how reinforcement learning can be used for vocabulary learning. I also present a model that uses neural collaborative filtering to learn student knowledge representations. Lastly, I present a state-of-the-art model to predict the probability of vocabulary word recall for students learning English as a second language. The system's novelty lies in the use of word complexity to adapt the forgetting curve as well as its incorporation of psychological theory to select an appropriate model

Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference

In modern computer science education, massive open online courses (MOOCs) log thousands of hours of data about how students solve coding challenges. Being so rich in data, these platforms have garnered the interest of the machine learning community, with many new algorithms attempting to autonomously provide feedback to help future students learn. But what about those first hundred thousand students? In most educational contexts (i.e. classrooms), assignments do not have enough historical data for supervised learning. In this paper, we introduce a human-in-the-loop "rubric sampling" approach to tackle the "zero shot" feedback challenge. We are able to provide autonomous feedback for the first students working on an introductory programming assignment with accuracy that substantially outperforms data-hungry algorithms and approaches human level fidelity. Rubric sampling requires minimal teacher effort, can associate feedback with specific parts of a student's solution and can articulate a student's misconceptions in the language of the instructor. Deep learning inference enables rubric sampling to further improve as more assignment specific student data is acquired. We demonstrate our results on a novel dataset from Code.org, the world's largest programming education platform.Comment: To appear at AAAI 2019; 9 page

Developing professional skills in journalism through blogs

The curriculum for journalism is being forced to change because the traditional print-based and broadcast modes are being challenged by wide and easy access to online mass communication. Primarily, students need to develop proficiency in writing, editing and publishing. However, they are also expected to be skilled in the Web medium as they venture into their careers, and weblogs offer a dynamic platform to develop these skills. Based on a statistical summary of student comments on the performance criteria for a blog project, a focus group interview and survey results, this paper will discuss the findings from the introduction of a course-based blog to an undergraduate course in Hong Kong, including: (1) the technical challenge of making Web features; (2) the perception of proficiency in online publishing; (3) the evaluative skills developed through a peer-review process; and (4) the development of a learning community through writing in blogs. © 2011 Taylor & Francis.postprin