This paper presents the development of a Sinhala-Tamil bilingual parallel corpus with sentence-level alignment. The corpus comprises source language text from contemporary writings, with all sentences translated manua...
ISBN:
(纸本)9783031705625;9783031705632
This paper presents the development of a Sinhala-Tamil bilingual parallel corpus with sentence-level alignment. The corpus comprises source language text from contemporary writings, with all sentences translated manually. Active learning methods were employed to select sentences, ensuring the representation of effective language structures in both languages. The corpus is divided into two parts: one with translations from Sinhala to Tamil direction, consisting of 25k parallel sentences, while the other consists of translations from Tamil to Sinhala direction, comprising 22k parallel sentences. Manual translations were conducted by two teams of professional translators. The resulting final version of TamSiPara, the Tamil-Sinhala bilingual parallel corpus consists of a total of 47k parallel sentences.
The recent increase in data and model scale for language model pre-training has led to huge training costs. In scenarios where new data become available over time, updating a model instead of fully retraining it would...
ISBN:
(纸本)9783031705625;9783031705632
The recent increase in data and model scale for language model pre-training has led to huge training costs. In scenarios where new data become available over time, updating a model instead of fully retraining it would therefore provide significant gains. We study the pros and cons of updating a language model when new data comes from new languages - the case of continual learning under language shift. Starting from a monolingual English language model, we incrementally add data from Danish, Icelandic and Norwegian to investigate how forward and backward transfer effects depend on pre-training order and characteristics of languages, for models with 126M, 356M and 1.3B parameters. Our results show that, while forward transfer is largely positive and independent of language order, backward transfer can be positive or negative depending on the order and characteristics of new languages. We explore a number of potentially explanatory factors and find that a combination of language contamination and syntactic similarity best fits our results.
Student agency is a key educational goal increasingly being impacted by artificialintelligence (AI) systems integrated into the human learning process. In September 2023, the Ministers responsible for education decid...
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ISBN:
(纸本)9783031642982;9783031642999
Student agency is a key educational goal increasingly being impacted by artificialintelligence (AI) systems integrated into the human learning process. In September 2023, the Ministers responsible for education decided to develop two policy instruments to regulate AI in education, setting teacher and learner agency as a policy goal. To examine how agency for AI regulation in the Europe is understood in policy discourse, I conducted an inductive content analysis of the documents that serve as a basis for these policy instruments. Using documents referred to in Resolution Three on Harnessing the Potential for AI in and through Education as the basis for analysis, five main areas of agency implementation were identified: ethics, AI literacy, regulations, pedagogy, and the capacity to exercise rights and attributes within each field. Key findings, three strains for agency, can guide policy makers and educational practitioners to define actors' roles and responsibility when using AI in the classroom. Different areas of implementation and attributes of agency exist, which will likely guide decision-making and design of policy instruments to assess and ensure agency when AI is employed in an educational context.
Multiple Choice Questions (MCQs) are frequently used for educational assessments for their efficiency in grading and providing feedback. However, manually generatingMCQs has some limitations and challenges. This study...
ISBN:
(纸本)9783031642982;9783031642999
Multiple Choice Questions (MCQs) are frequently used for educational assessments for their efficiency in grading and providing feedback. However, manually generatingMCQs has some limitations and challenges. This study explores an AI-driven approach to creating and evaluating Bloom's Taxonomy-aligned college-level biology MCQs using a varied number of shots in few-shot prompting with GPT-4. Shots, or examples of correct prompt-response pairs, were sourced from previously published datasets containing educator-approved MCQs labeled with their Bloom's taxonomy and were matched to prompts via a maximal marginal relevance search. To obtain ground truths to compare GPT-4 against, three expert human evaluators with a minimum of 4 years of educational experience annotated a random sample of the generated questions with regards to relevance to the input prompt, classroom usability, and perceived Bloom's Taxonomy level. Furthermore, we explored the feasibility of an AI-driven evaluation approach that can rate question usability using the Item Writing Flaws (IWFs) framework. We conclude that GPT-4 generally shows promise in generating relevant and usable questions. However, more work needs to be done to improve Bloom-level alignment accuracy (accuracy of alignment between GPT-4's target level and the actual level of the generated question). Moreover, we note that a general inverse relationship exists between alignment accuracy and number of shots. On the other hand, no clear trend between shot number and relevance/usability was observed. These findings shed light on automated question generation and assessment, presenting the potential for advancements in AI-driven educational evaluation methods.
This paper delves into the functionalities of an Intelligent Pilot Advisory System (IPAS) in normal aviation operations. Building upon the foundational work of "Intelligent Pilot Advisory System: The Journey From...
ISBN:
(纸本)9783031607271;9783031607288
This paper delves into the functionalities of an Intelligent Pilot Advisory System (IPAS) in normal aviation operations. Building upon the foundational work of "Intelligent Pilot Advisory System: The Journey From Ideation to an Early System Design of an AI-Based Decision Support System for Airline Flight Decks" by Jakob Wurfel et al., which primarily focused on emergency scenarios, this study extends the IPAS's application to non-emergency contexts. Utilizing a user-centered approach, a workshop involving pilots, data scientists, and Human-artificialintelligence Teaming (HAT) experts was conducted to brainstorm and evaluate functionalities for this system in regular flight operations. The methodology combined creative and analytical techniques, including the 6-3-5 ideation method, mind mapping and design studio method, leading to rapid prototyping and iterative feedback. During the workshop, several key functionalities for the IPAS were identified, such as the Mission Monitoring and Advisory Function (MMAF), which provides real-time updates on flight-related factors, as well as the integration of pre-flight briefing and operational guidance. Based on the workshops results an early prototype was developed, showcasing a timeline-based presentation of information and interactive user interface elements. This prototype serves as the basis for initial feedback evaluation and ongoing refinement. By integrating AI and leveraging the amount of aviation data, this intelligent advisor aims to improve situational awareness, decision-making, and operational efficiency in normal flight operations. In this context, this paper highlights the need for extended pilot testing and integration with existing cockpit systems, emphasizing the importance of human-AI teaming aspects, customization, data security, and the system's impact on pilot skills, training and the environment.
The information of semantic roles can reflect important characteristics of verbs. Among verbs related to animals actions, suffocate verbs have received limited attention in the fields of linguistics and language teach...
ISBN:
(纸本)9789819705825;9789819705832
The information of semantic roles can reflect important characteristics of verbs. Among verbs related to animals actions, suffocate verbs have received limited attention in the fields of linguistics and language teaching. This study has selected five suffocate verbs and analyzed 305 single sentences containing them from corpora. The results show that the verb (sic) zhixi 'suffocate' has both agentlike semantic roles and patient-like semantic roles, whereas the other 4 verbs only have agent-like semantic roles according to the analyzed sentences. Additionally, only (sic) zhixi 'suffocate' appears in the causative alternation. The common situational roles of suffocate verbs include Manner, Time, and Location. This paper is conducive to the enriching the research on suffocate verbs and provides an important reference for lexicography.
This work investigates how tutoring discourse interacts with students' proximal knowledge to explain and predict students' learning outcomes. Our work is conducted in the context of high-dosage human tutoring ...
ISBN:
(纸本)9783031642982;9783031642999
This work investigates how tutoring discourse interacts with students' proximal knowledge to explain and predict students' learning outcomes. Our work is conducted in the context of high-dosage human tutoring where 9th-grade students (N = 1080) attended small group tutorials and individually practiced problems on an Intelligent Tutoring System (ITS). We analyzed whether tutors' talk moves and students' performance on the ITS predicted scores on math learning assessments. We trained Random Forest Classifiers (RFCs) to distinguish high and low assessment scores based on tutor talk moves, student's ITS performance metrics, and their combination. A decision tree was extracted from each RFC to yield an interpretable model. We found AUCs of 0.63 for talk moves, 0.66 for ITS, and 0.77 for their combination, suggesting interactivity among the two feature sources. Specifically, the best decision tree emerged from combining the tutor talk moves that encouraged rigorous thinking and students' ITS mastery. In essence, tutor talk that encouraged mathematical reasoning predicted achievement for students who demonstrated high mastery on the ITS, whereas tutors' revoicing of students' mathematical ideas and contributions was predictive for students with low ITS mastery. Implications for practice are discussed.
Guai zhi guai(sic) is a relatively common and special fixed phrase in modern Chinese oral expressions, which is actually a cross-layer lexical product obtained by intercepting and condensing on the basis of hypothetic...
ISBN:
(纸本)9789819705825;9789819705832
Guai zhi guai(sic) is a relatively common and special fixed phrase in modern Chinese oral expressions, which is actually a cross-layer lexical product obtained by intercepting and condensing on the basis of hypothetical conditional complex sentences. About it's part-of-speech function, guai zhi guai is a component between verbs and conjunctions, or a verbal fixed phrase with a connect function. From the perspective of semantic function, the basic semantic function of guai zhi guai is the meaning of blame. After the pragmatic function has been expanded, a sigh function has been added to convey the speaker's subjective stance and emotion. In addition, by comparing some similar structures, for example guai zhi guai, yao guai zhi guai(sic) and yao guai zhi neng guai(sic), zhi guai(sic), dou guai(sic), quan guai(sic), jiu guai(sic), we found that guai zhi guai and jiu guai have a higher degree of lexicalization, which can convey more prominent subjective meanings.
In this study, upper-elementary-age students used an interactive reading app to read from a classic children's novel during a summer program. Students took turns reading with an adult virtual narrator (audiobook)....
ISBN:
(纸本)9783031642982;9783031642999
In this study, upper-elementary-age students used an interactive reading app to read from a classic children's novel during a summer program. Students took turns reading with an adult virtual narrator (audiobook). We use process and background data to explore factors that could predict whether a reader will read their next turn or skip it. We find that skipping quickly becomes self-perpetuating, underscoring the need to support the teacher in providing just-in-time personalized intervention to help students avoid the disengagement trap.
Manipulating objects with a robotic hand or gripper is a challenging task that can be supported by knowledge about the object, such as textual descriptions. Even with such knowledge, there remain numerous possibilitie...
ISBN:
(纸本)9783031705656;9783031705663
Manipulating objects with a robotic hand or gripper is a challenging task that can be supported by knowledge about the object, such as textual descriptions. Even with such knowledge, there remain numerous possibilities for applying an appropriate grasping gesture. This ambiguity can be reduced by providing information about the intended task, aiding robots in making the choice of a suitable grasp less arbitrary and more robust. This work investigates using word embeddings in the context of grasp classification for multi-fingered robots. Instead of predicting grasping gestures without specifying the intended task, our work combines a description of the properties of an object and task-related information. We demonstrate that a systematically generated dataset and fine-tuned context embeddings can compete with existing models that do not consider object manipulation. Our best model achieves a micro f1 score of 0.774 and macro f1 score of 0.731 while distinguishing between over 40 tasks.
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