標題: Titlebook: Artificial Intelligence in Education; 22nd International C Ido Roll,Danielle McNamara,Vania Dimitrova Conference proceedings 2021 Springer [打印本頁] 作者: BULB 時間: 2025-3-21 19:45
書目名稱Artificial Intelligence in Education影響因子(影響力)
書目名稱Artificial Intelligence in Education影響因子(影響力)學(xué)科排名
書目名稱Artificial Intelligence in Education網(wǎng)絡(luò)公開度
書目名稱Artificial Intelligence in Education網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Artificial Intelligence in Education被引頻次
書目名稱Artificial Intelligence in Education被引頻次學(xué)科排名
書目名稱Artificial Intelligence in Education年度引用
書目名稱Artificial Intelligence in Education年度引用學(xué)科排名
書目名稱Artificial Intelligence in Education讀者反饋
書目名稱Artificial Intelligence in Education讀者反饋學(xué)科排名
作者: Affectation 時間: 2025-3-21 21:24 作者: hardheaded 時間: 2025-3-22 02:49
https://doi.org/10.1007/978-3-658-10552-5ying on a qualitative coding to analyze the transcripts. Our results shed light on how different levels of assistance provided by a computer tutor impact student reasoning during code-tracing activities.作者: 尖酸一點 時間: 2025-3-22 08:01 作者: 削減 時間: 2025-3-22 10:13 作者: 描繪 時間: 2025-3-22 15:10
Frank Hannes,Thorsten Kuhn,Miriam Brückmannthe construction of interpretable clustering of students’ solutions in problem-solving activities. We describe a specific realization of the algorithm for introductory Python programming and report results of the evaluation on a diverse set of problems.作者: 排他 時間: 2025-3-22 17:28 作者: Resign 時間: 2025-3-23 00:16 作者: SMART 時間: 2025-3-23 05:04 作者: maintenance 時間: 2025-3-23 05:52 作者: 值得贊賞 時間: 2025-3-23 09:45 作者: 殺死 時間: 2025-3-23 13:57
Engendering Trust in Automated Feedback: A Two Step Comparison of?Feedbacks in Gesture Based Learninmated feedback as it may not be as good as the manual feedback. We use an ASL learning application that provides fine grained explainable feedback and follow a two step process to present a comparison between the automated feedback and the manual feedback provided by experts.作者: micturition 時間: 2025-3-23 19:02 作者: 歌唱隊 時間: 2025-3-24 02:01
Frank Hannes,Thorsten Kuhn,Miriam Brückmannresponse datasets. We also qualitatively evaluate their ability in identifying common student errors in the form of clusters of incorrect options across different questions that correspond to the same error.作者: 萬花筒 時間: 2025-3-24 04:45 作者: Pageant 時間: 2025-3-24 09:12 作者: 壓碎 時間: 2025-3-24 13:43
Evaluating Critical Reinforcement Learning Framework in the Fieldcal-RL framework is empirically evaluated from two perspectives: whether optimal actions . be carried out in critical states (.) and whether only carrying out optimal actions in critical states is as effective as a fully-executed RL policy (.). Our results confirmed both hypotheses.作者: 總 時間: 2025-3-24 17:58 作者: 看法等 時間: 2025-3-24 19:45 作者: 強行引入 時間: 2025-3-24 23:10 作者: Fortuitous 時間: 2025-3-25 07:20
RepairNet: Contextual Sequence-to-Sequence Network for Automated Program Repair repair such errors can be a useful aid to the developers for their productivity. In this work, we propose a deep generative model, RepairNet, that automatically repairs programs that fail at compile time. RepairNet is based on sequence-to-sequence modeling and uses both code and error messages to r作者: debouch 時間: 2025-3-25 10:17 作者: CARE 時間: 2025-3-25 15:02
A Systematic Review of Data-Driven Approaches to Item Difficulty Predictionan determine items and tests’ overall quality. Therefore, . is extremely important in any pedagogical learning environment. Data-driven approaches to item difficulty prediction are gaining more and more prominence, as demonstrated by the recent literature. In this paper, we provide a systematic revi作者: 易彎曲 時間: 2025-3-25 18:09 作者: 虛度 時間: 2025-3-25 20:57
Affect-Targeted Interviews for Understanding Student Frustrationrceptions about the learning activity drive their experience of frustration and their subsequent choices during learning. In this paper, we adopt a mixed-methods approach, using automated detectors of affect to signal classroom researchers to interview a specific student at a specific time. We hand-作者: ethnology 時間: 2025-3-26 03:25
Explainable Recommendations in a Personalized Programming Practice Systemnalized practice system for introductory Java programming. We present the design of two types of explanations to justify recommendation of next learning activity to practice. The value of these explainable recommendations was assessed in a semester-long classroom study. The paper analyses the observ作者: 螢火蟲 時間: 2025-3-26 06:59
Multilingual Age of Exposureore creating more complex models of assessing text difficulty, the basic building block of a text consists of words and, inherently, its overall difficulty is greatly influenced by the complexity of underlying words. One approach is to measure a word’s Age of Acquisition (AoA), an estimate of the av作者: 使高興 時間: 2025-3-26 12:13 作者: 不理會 時間: 2025-3-26 16:20 作者: outskirts 時間: 2025-3-26 18:42
Adaptively Scaffolding Cognitive Engagement with Batch Constrained Deep Q-Networksh a learning activity in terms of four different engagement modes—Interactive, Constructive, Active, and Passive—and it predicts that increased cognitive engagement will yield improved learning. However, a key open question is how best to translate the ICAP theory into the design of adaptive scaffol作者: cringe 時間: 2025-3-27 00:44
Ordering Effects in a Role-Based Scaffolding Intervention for Asynchronous Online Discussionsous discussions. Previous work has demonstrated how this type of scaffolding can result in student contributions of greater depth and quality. However, since students necessarily experience the roles in varying orders, it is important to consider whether the ordering impacts the outcome. This paper 作者: Insul島 時間: 2025-3-27 03:38
Option Tracing: Beyond Correctness Analysis in Knowledge Tracingtions. One key limitation of most existing knowledge tracing methods is that they can only estimate an . knowledge level of a student per knowledge component/skill since they analyze only the (usually binary-valued) correctness of student responses. Therefore, it is hard to use them to diagnose spec作者: 翻動 時間: 2025-3-27 07:22 作者: Vo2-Max 時間: 2025-3-27 12:18
Discovering Co-creative Dialogue States During Collaborative Learning, and very little is known about the dialogue mechanisms that support learning during collaborative co-creativity. To address this need, we analyzed the structure of collaborative dialogue between pairs of high school students who co-created music by writing code. We used hidden Markov models to ana作者: WATER 時間: 2025-3-27 15:21 作者: figurine 時間: 2025-3-27 19:01 作者: cruise 時間: 2025-3-27 23:19
Investigating Students’ Reasoning in a Code-Tracing Tutorsight into students’ cognitive processes as they used a computer tutor to study code-tracing examples and work on code-tracing problems, using either a high-scaffolding or a reduced-scaffolding tutor interface. For the cognitive processes, we included both self-explanation and reading behaviors, rel作者: Aggrandize 時間: 2025-3-28 03:16
Evaluating Critical Reinforcement Learning Framework in the Fielded great success in inducing effective pedagogical policies for various interactive e-learning environments. However, it is often prohibitive to identify the . pedagogical decisions that actually contribute to desirable learning outcomes. In this work, by utilizing the RL framework we defined . to b作者: MAIM 時間: 2025-3-28 09:28
Artificial Intelligence in Education978-3-030-78292-4Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 衍生 時間: 2025-3-28 14:23
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/162434.jpg作者: HAUNT 時間: 2025-3-28 18:04
Bemerkenswerte Familienunternehmen, repair such errors can be a useful aid to the developers for their productivity. In this work, we propose a deep generative model, RepairNet, that automatically repairs programs that fail at compile time. RepairNet is based on sequence-to-sequence modeling and uses both code and error messages to r作者: 休閑 時間: 2025-3-28 22:20
https://doi.org/10.1007/978-3-322-84233-6sistence, when students are working in online learning system. This work has, in cases, treated any student who completes more than ten items on a topic without mastering it as being in need of intervention. By contrast, the broader fields of education and human development have recognized the value作者: 群島 時間: 2025-3-29 02:32 作者: 期滿 時間: 2025-3-29 06:52 作者: Relinquish 時間: 2025-3-29 08:56
Frank Hannes,Thorsten Kuhn,Miriam Brückmannrceptions about the learning activity drive their experience of frustration and their subsequent choices during learning. In this paper, we adopt a mixed-methods approach, using automated detectors of affect to signal classroom researchers to interview a specific student at a specific time. We hand-作者: Chemotherapy 時間: 2025-3-29 14:48
Frank Hannes,Thorsten Kuhn,Miriam Brückmannnalized practice system for introductory Java programming. We present the design of two types of explanations to justify recommendation of next learning activity to practice. The value of these explainable recommendations was assessed in a semester-long classroom study. The paper analyses the observ作者: 斷言 時間: 2025-3-29 17:08 作者: 無聊點好 時間: 2025-3-29 21:33 作者: 異端邪說2 時間: 2025-3-30 00:11
Frank Hannes,Thorsten Kuhn,Miriam Brückmannr applications in student modeling, it is useful to find structure in the set of all submitted solutions. We propose a generic, modular algorithm for the construction of interpretable clustering of students’ solutions in problem-solving activities. We describe a specific realization of the algorithm作者: minion 時間: 2025-3-30 04:51
https://doi.org/10.1007/978-3-8349-9558-2h a learning activity in terms of four different engagement modes—Interactive, Constructive, Active, and Passive—and it predicts that increased cognitive engagement will yield improved learning. However, a key open question is how best to translate the ICAP theory into the design of adaptive scaffol作者: Ventilator 時間: 2025-3-30 11:28
https://doi.org/10.1007/978-3-8349-9558-2ous discussions. Previous work has demonstrated how this type of scaffolding can result in student contributions of greater depth and quality. However, since students necessarily experience the roles in varying orders, it is important to consider whether the ordering impacts the outcome. This paper 作者: 繁榮中國 時間: 2025-3-30 12:46
Frank Hannes,Thorsten Kuhn,Miriam Brückmanntions. One key limitation of most existing knowledge tracing methods is that they can only estimate an . knowledge level of a student per knowledge component/skill since they analyze only the (usually binary-valued) correctness of student responses. Therefore, it is hard to use them to diagnose spec作者: FAST 時間: 2025-3-30 17:15 作者: sterilization 時間: 2025-3-30 20:59
,Die Unternehmerfamilie – ein Mythos?,, and very little is known about the dialogue mechanisms that support learning during collaborative co-creativity. To address this need, we analyzed the structure of collaborative dialogue between pairs of high school students who co-created music by writing code. We used hidden Markov models to ana作者: 猛然一拉 時間: 2025-3-31 01:32 作者: Suppository 時間: 2025-3-31 08:47
D Zusammenfassung und Ausblick,n doors for newer opportunities in gesture based learning and practice, the effectiveness of these feedback as compared to manual feedback remains as a question in the minds of the users. For learners of American Sign Language (ASL), automated feedback generated by an application often causes a sens作者: Sputum 時間: 2025-3-31 10:39
https://doi.org/10.1007/978-3-658-10552-5sight into students’ cognitive processes as they used a computer tutor to study code-tracing examples and work on code-tracing problems, using either a high-scaffolding or a reduced-scaffolding tutor interface. For the cognitive processes, we included both self-explanation and reading behaviors, rel作者: 繁殖 時間: 2025-3-31 14:16
Arnold Weissman,Pascal Barreuthered great success in inducing effective pedagogical policies for various interactive e-learning environments. However, it is often prohibitive to identify the . pedagogical decisions that actually contribute to desirable learning outcomes. In this work, by utilizing the RL framework we defined . to b作者: Afflict 時間: 2025-3-31 19:53
https://doi.org/10.1007/978-3-030-78292-4artificial intelligence; computer aided instruction; computer programming; computer systems; computer vi作者: condone 時間: 2025-3-31 23:09 作者: 無脊椎 時間: 2025-4-1 03:22 作者: exhibit 時間: 2025-4-1 08:32
Annotating Student Engagement Across Grades 1–12: Associations with Demographics and Expressivityed with age, and critically, rotational head movements mediated the effects of grade on behavioral IRR; there was no mediation for emotional IRR. There were no effects of gender or ethnicity on IRR. We discuss the implications of our findings for annotating engagement in supervised learning models f作者: 他去就結(jié)束 時間: 2025-4-1 12:56
Affect-Targeted Interviews for Understanding Student Frustrationving strategies. We conclude with thoughts on both how this can influence the future design of AIED systems, and the broader potential uses of data mining-driven interviews in AIED research and development.作者: 享樂主義者 時間: 2025-4-1 16:10
