Context Of Dialogue Research Articles

Domain Adversarial Network for Cross-Domain Emotion Recognition in Conversation

Emotion Recognition in Conversation (ERC) aims to recognize the emotion for each utterance in a conversation automatically. Due to the difficulty of collecting and labeling, this task lacks the dataset corpora available on a large scale. This increases the difficulty of finishing the supervised training required by large-scale neural networks. Introducing the large-scale generative conversational dataset can assist with modeling dialogue. However, the spatial distribution of feature vectors in the source and target domains is inconsistent after introducing the external dataset. To alleviate the problem, we propose a Domain Adversarial Network for Cross-Domain Emotion Recognition in Conversation (DAN-CDERC) model, consisting of domain adversarial and emotion recognition models. The domain adversarial model consists of the encoders, a generator and a domain discriminator. First, the encoders and generator learn contextual features from a large-scale source dataset. The discriminator performs domain adaptation by discriminating the domain to make the feature space of the source and target domain consistent, so as to obtain domain invariant features. Then DAN-CDERC transfers the learned domain invariant dialogue context knowledge from the domain adversarial model to the emotion recognition model to assist in modeling the dialogue context. Due to the use of a domain adversarial network, DAN-CDERC obtains dialogue-level contextual information that is domain invariant, thereby reducing the negative impact of inconsistency in domain space. Empirical studies illustrate that the proposed model outperforms the baseline models on three benchmark emotion recognition datasets.

Towards retrieval-based conversational recommendation

Conversational recommender systems (CRS) have attracted immense attention in the past few years. The most recent approaches rely on neural models trained on recorded dialogs between humans, implementing an end-to-end learning process. These systems are commonly designed to generate responses given the user’s utterances in natural language. One main challenge is that these generated responses both have to be appropriate for the given dialog context and must be grammatically and semantically correct. Recent studies however highlighted that current generation-based systems often struggle to provide such responses. An alternative to generation-based approaches is to retrieve responses from pre-recorded dialog data and to adapt them if needed. Such retrieval-based approaches were successfully explored in the context of general conversational systems, but have received limited attention in recent years for CRS. In this work, we re-assess the potential of such approaches and design and evaluate a novel technique for response retrieval and ranking. A user study (N = 90) revealed that the responses by our system were on average of higher quality than those of two recent generation-based systems. We furthermore found that the quality ranking of the two generation-based approaches is not aligned with the results from the literature, which points to open methodological questions. Overall, our research underlines that retrieval-based approaches should be considered an alternative or complement to language generation approaches.11This work continues and significantly extends our research presented in Manzoor and Jannach (2021).

Cultural Discourse in Indonesian Humor: A Case Study of Some Short Dialogues

This study aims to describe cultural discourse in Indonesian humor. Cultural discourse is the relationship between the meaning of a dialogue context and the cultural context of the listener or recipient of humor. Indonesia is a nation that has a distinctive humor and rhetorical style. Rhetoric style like this is one type of stylistic aspect in communication. The purpose of this research is formulated to 1) to show cultural discourse of humor in dialogues and it category, and 2) to describe the respondent's perception of humor in dialogue as a means of entertainment. The data of this research are humorous discourses in the form of dialogues which are very often found in social interactions and social media. Data analysis was carried out by using Berger's theory of humor. This theory divides humor into categories based on the dialogues in humor. The results showed that the humor category was divided into language category 14 (56%) following logic category 8 (32%), and identity category 3 (12%). Of respondents' perceptions, very funny was at 55.6%, followed by funny 33.3%, and quite funny only reached 11.1%. This perception is closely related to the respondent's cultural conception. The implication of this research shows that humorous discourse has a rhetorical structure and pattern of expression so as to create a sense of humor that is entertaining for readers and listeners.

From the Definition of Colours Attributes to Build a Semantic Space: Application to a Sport-Health Dialogical Context of Use

AbstractThe integration of user perception into the design process has become necessary to provide the best experience to users. All methods focusing on the interpretations of products are based on the same principle: identifying relationships between a semantics and physical attributes of products within a product domain. Sometimes this domain makes the definition of these relations more complex as for a dialogic context of us due to the lack of existing product. We propose in this paper a method to define a semantics directly from products attributes in regards with a dialogic product domain.

Understanding Design Features of Music and Language: The Choric/Dialogic Distinction.

Music and spoken language share certain characteristics: both consist of sequences of acoustic elements that are combinatorically combined, and these elements partition the same continuous acoustic dimensions (frequency, formant space and duration). However, the resulting categories differ sharply: scale tones and note durations of small integer ratios appear in music, while speech uses phonemes, lexical tone, and non-isochronous durations. Why did music and language diverge into the two systems we have today, differing in these specific features? We propose a framework based on information theory and a reverse-engineering perspective, suggesting that design features of music and language are a response to their differential deployment along three different continuous dimensions. These include the familiar propositional-aesthetic (‘goal’) and repetitive-novel (‘novelty’) dimensions, and a dialogic-choric (‘interactivity’) dimension that is our focus here. Specifically, we hypothesize that music exhibits specializations enhancing coherent production by several individuals concurrently—the ‘choric’ context. In contrast, language is specialized for exchange in tightly coordinated turn-taking—‘dialogic’ contexts. We examine the evidence for our framework, both from humans and non-human animals, and conclude that many proposed design features of music and language follow naturally from their use in distinct dialogic and choric communicative contexts. Furthermore, the hybrid nature of intermediate systems like poetry, chant, or solo lament follows from their deployment in the less typical interactive context.

NARRATIVE ESSENCE OF LANGUAGE CONTENT IN COMPOSERS’ EVALUATION OF THEIR CREATIVITY

The paper investigates the narratives of contemporary Ukrainian composers, in the context of their assessment of their own work and the actual musicological components of each work: its focus, conglomeration of musical expressive means, and their multidimensional and multifunctional context. The paper focuses on the problem of inconsistency of the author’s linguistic content in expressing his own ideas about his work with the actual work in terms of the logic of musicology, psychology, etc. A new narrative approach to the interpretation of musical expressive means has formed in modern compositional work. They are viewed as the combinations of different levels of perception: visual, sensory, linguistic, associative-ambiguous, abstract, etc. Thus, wherever there is an information and communicative environment, there function the complex cognitive formations allowing to reflect and evaluate the imagery of the musical work. Hence, the “conceptual sphere” of each work emerges that consists of the relevant ideas, concepts, images, and statements. The research methodology is based on the analysis of the sphere of expression of human thinking and communicative processes by R. Barthes, C. Bremond, F. Jameson, T. Titarenko, T. Todorov, E. Tshebinsky, and others. Also, the studies by H.-G. Gadamer, M. Heidegger, P. Ricoeur, R. Harré consider the narrative as a discursive structure formed on the basis of personal experience. In the field of musical art, the problem of narratology was addressed in the works of N. Gerasimova-Persidska, O. Zinkevych, Y. Chekan, and some other musicologists who expressed the essence of modern compositional thinking, in line with a new sense of time and space, discreteness and dialogic historical context of culture. To establish the artistic conceptuality of certain musical pieces, the comparative analysis of subjective and authorial understanding of composers of their own works in the musicological, cultural, and socio-political context was made. As the works have a significant number of allusions to the stylistics of different eras, the conflicting emotional reaction of the composers gives grounds to assert the idea of expressing a narrative of existential torment of a torn postmodern mind in the inter-genre web in their works. The paper concludes that assimilation and awareness of meaning are possible only through certain messages that can have many meanings, and complex decoding of them may take any form. Perception of oneself in the social environment occurs through the formation of narratives that express the author’s position. However, this stance voiced in interviews and other language content is not always consistent with the actual music series. Thus, an interpretive understanding of musical creativity emerges at the junction of the narrator’s and the listener’s meanings.

Review: Genocide in Libya: Shar, A Hidden Colonial History, by Ali Abdullatif Ahmida

Review: <i>Genocide in Libya: Shar, A Hidden Colonial History</i>, by Ali Abdullatif Ahmida

Revisiting audio visual scene-aware dialog

Audio Visual Scene-Aware Dialog (AVSD) has drawn intense interests, in which models are required to understand dynamic scenes in videos and dialog contexts in order to converse with human users by generating responses to given questions. Existing works have laid a solid foundation towards solving the AVSD problem. In contrast to previous studies, this paper empirically revisits the AVSD task and argues that this task exhibits a variety of biases in terms of models, dataset, and evaluation metrics: (1) as for the models, we believe that the state-of-the-art frameworks do not utilize multimodal features to their full extent; (2) as for the dataset, we conduct a deep analysis into dataset statistics from different types of questions and find that the dataset is slightly biased in several specific aspects; by simply implementing a caption-only baseline that has never seen the video, we achieve state-of-the-art performance on the AVSD task; (3) as for the evaluation metrics, we argue that the current metrics for AVSD primarily focus on the naturalness of generated responses while ignoring the truthfulness, which makes them fall short of disclosing the consistency of model predictions and the actual visual content. Overall, our analysis aims to provide a detailed inspection of the AVSD task and we hope that our empirical observations can inspire further improvement to the task.

A multiturn complementary generative framework for conversational emotion recognition

Conversational emotion recognition (CER) is a significant task due to its application in human–computer interaction. Existing work treats CER as an utterance-level classification task without considering that empathic response also reflects contextual emotion understanding. Previous work has proven that accurate recognition of emotions in the dialogue history is helpful to generate high-fit responses. In this paper, we investigate whether this conclusion is a sufficient and necessary condition. Specifically, we define an auxiliary empathic multiturn dialogue generation (MDG) task to enhance emotion understanding. Correspondingly, we present a Sequence-to-Sequence oriented framework that combines CER and MDG in a multitask learning manner to verify the complementarity between the two tasks. First, we use alternate recurrent neural networks to encode the content of historical utterances and represent the states of multiparty emotions, which are used for emotion classification. Second, since most MDG methods ignore the emotional coherence of the dialogue context itself, we use affine transformation to fuse hidden states of content and emotions to initialize the decoder. Finally, at each step of generation, an attention mechanism is used to fuse information from the dialogue history to ensure emotional coherence. The CER results of our models outperform the state-of-the-art on three prevalent emotional dialogue data sets. Further analysis demonstrates the mutual promotion and empathy interpretability between MDG and CER. Furthermore, our framework is scalable for different coding strategies and multimodal fusion. To the best of our knowledge, this is the first work to explore CER from the perspective of empathy through multitask learning with dialogue generation.

Exploiting Pairwise Mutual Information for Knowledge-Grounded Dialogue

External document knowledge is helpful for dialogue systems to generate high-quality responses. Although several knowledge-grounded dialogue models have been designed, external knowledge cannot be comprehensively exploited due to the complex relationships among dialogue context, knowledge, and responses. To this end, we propose a novel transformer-based model, named TransIKG, which incorporates external document knowledge for dialogue generation. TransIKG comprises a two-step integration mechanism, including correlation integration and overall integration. Correlation integration is designed to fully exploit the pairwise mutual information among dialogue context, knowledge, and responses, while overall integration adopts an integration gate to capture global information. Furthermore, we utilize the positional information of dialogue turns to better represent the dialogue context and enhance the generalization ability of our model on out-of-domain documents. Finally, we propose a novel knowledge-aware pointer network to generate knowledge-enhanced response tokens. Experimental results on two benchmark datasets demonstrate that our model outperforms state-of-the-art models on both open-domain and domain-specific dialogues.

Domain-Slot Relationship Modeling Using a Pre-Trained Language Encoder for Multi-Domain Dialogue State Tracking

Dialogue state tracking for multi-domain dialogues is challenging because the model should be able to track dialogue states across multiple domains and slots. As using pre-trained language models is the de facto standard for natural language processing tasks, many recent studies use them to encode the dialogue context for predicting the dialogue states. Model architectures that have certain inductive biases for modeling the relationship among different domain-slot pairs are also emerging. Our work is based on these research approaches on multi-domain dialogue state tracking. We propose a model architecture that effectively models the relationship among domain-slot pairs using a pre-trained language encoder. Inspired by the way the special [CLS] token in BERT is used to aggregate the information of the whole sequence, we use multiple special tokens for each domain-slot pair that encodes information corresponding to its domain and slot. The special tokens are run together with the dialogue context through the pre-trained language encoder, which effectively models the relationship among different domain-slot pairs. Our experimental results on the datasets MultiWOZ-2.0 and MultiWOZ-2.1 show that our model outperforms other models with the same setting. Our ablation studies incorporate three main parts. The first component shows the effectiveness of our approach exploiting the relationship modeling. The second component compares the effect of using different pre-trained language encoders. The final component involves comparing different initialization methods that could be used for the special tokens. Qualitative analysis of the attention map of the pre-trained language encoder shows that our special tokens encode relevant information through the encoding process by attending to each other.

Generating Rational Commonsense Knowledge-Aware Dialogue Responses With Channel-Aware Knowledge Fusing Network

Dialogues systems endow machines with the ability to converse with humans using natural language. Nonetheless, previous Seq2Seq-based generative dialogue systems often generate safe but meaningless responses, such as &#x2018;I don&#x0027;t know&#x0027; or &#x2018;I think so&#x0027;. To this end, researchers proposed to infuse external knowledge into dialogue generation, and such knowledge-enhanced methods have achieved remarkable improvements in the open-domain dialogue systems. External knowledge is an exogenous input, where the estrangement inevitably exists between knowledge and dialogue context. Although previous knowledge-enhanced works can already use commonsense knowledge to generate informative responses, they always use knowledge in a single-channel paradigm, which is hard to accurately handle different data-flows and then tends to generate irrational dialogue responses. Thus, they tend to be confused and generate strange responses when infusing the knowledge into dialogue generation, such as &#x2018;I just ate a basketball&#x2019;, dramatically degrading the user experience. To address this problem, this paper proposes a novel <i>Channel-Aware Knowledge Fusing</i> Network (CAKF). Rather than following the traditional single-channel paradigm, CAKF employs three unique channels to handle different data-flows more clearly and rationally: a <i>base</i> channel serves like a vanilla Seq2Seq decoder; a <i>context</i> channel to utilize the contextual information, and a <i>knowledge</i> channel to infuse commonsense knowledge into the dialogue generation. Above such three channels, a <i>Sequential Manager</i> is built to maintain the global sequential decision state, aggregate the local data-flows, and make the final prediction. Experiments on two open-released datasets (a Chinese Weibo and an English Reddit) demonstrated the superior performance of this work against various state-of-the-art approaches.

Slaying the “political vampire”: Aberration as a socio-political construct

The concept of vampirism in the tradition of peasant culture is an inversion of social norms by individuals or groups, which the community recognizes as responsible for social problems and crises. ?Vampire? as a social institution has a role in resolving the crisis, but also manifests power of the collective and the desirable model of worldview. However, the experience of field research imposes a perspective that does not perceive the ?vampire? as a rigid institution, but also an adaptable tool of social or political communication. By analyzing two cases (performances) of ?murder of a political vampire? (Josip Broz Tito and Slobodan Milosevic), as a performance of political communication, I try to point out the crucial importance of understanding the context, position and motivation of actors in dialogue. The focus of the analysis is on ?vampires?, the signifier of the aberrant, who uses vampire symbolism as a means of spreading political information but also achieving political goals.

Neural Network With Hierarchical Attention Mechanism for Contextual Topic Dialogue Generation

The encoder-decoder model has achieved remarkable results in natural language generation. However, in the dialogue generation work, we often ignore the influence of the dialogue context information and topic information in the generation, resulting in the generated replies not close to the context or lack of topic information leads to general responses. In this work, we study the generation of multi-turn dialogues based on a large corpus and take advantage of the context information and topic information of the conversation in the process of dialogue generation to generate more coherent context-sensitive responses. We improve upon existing models and attention mechanisms and propose a new hierarchical model to better solve the problem of dialogue context (the HAT model). This method enables the model to obtain more contextual information when processing and improves the ability of the model in terms of contextual relevance to produce high-quality responses. In addition, to address the absence of topics in the responses, we pre-train the LDA(Latent Dirichlet Allocation) topic model to extract topic words of the dialogue content and retain as much topic information of dialogue as possible. Our model is extensively tested in several corpora, and the experiments illustrate that our model is superior to most hierarchical and non-hierarchical models with respect to multiple evaluation metrics.

The specific features of the narrative structure of the epilogue to F. M. Dostoevsky’s novel "Crime and Punishment" (to the 200th anniversary of the birth)

The paper examines the narrative structure of the epilogue to the novel "Crime and Punishment" by F. M. Dostoevsky. The aim of the study is to describe the techniques employed by the author of the novel to actualise his final speech. The principal methods the research employs include general scientific methods (observation, comparison, and others), general philological methods (contextological, compositional, structural, and others), proper linguistic methods (semantic-stylistic, comparative stylistic, intertextual, and others). To reveal the specific features of the epilogue, the peculiarities of the author’s narration in the main body of "Crime and Punishment" were taken into consideration. In the first place, they are the "telling", dialogical nature, the presence of the author’s final speech. The comparative-contrastive study of the two parts of the epilogue in contrast to the rest of the novel facilitates the determination of the narration uniqueness in the epilogue. The subjective and chronotopic organisation of the final part of "Crime and Punishment" makes the tale move to a different level: the Christian system of coordinates becomes the world view basis of both the author-narrator and the protagonist (lifetime is measured in terms of church holidays, the "mundane" chronotope is replaced by the "Christian" one). The author’s voice in the epilogue is expressed both indirectly and directly, with the help of ironic and dialogic contexts. The author’s stand is manifested in the choice of words as well as in various symbolic details, and numerous references to the preceding contexts, and in the intertextual links of the novel.

РЕЗУЛЬТАТЫ ИССЛЕДОВАНИЯ ПРОЦЕССА ФОРМИРОВАНИЯ РЕФЛЕКСИВНЫХ УМЕНИЙ БУДУЩИХ МЕНЕДЖЕРОВ В СИСТЕМЕ СРЕДНЕГО ПРОФЕССИОНАЛЬНОГО ОБРАЗОВАНИЯ

Statement of the problem. The purpose of professional education is to provide managers with professional qualities which form the competence of an individual. In this context, much attention is paid to the formation of reflexive skills of future managers that contribute to understanding, awareness, analysis, and evaluation of large amount of information. The lack of universal understanding in Pedagogy of the features of the process of forming reflexive skills among future managers proves the relevance of this study. The purpose of the article is to identify the features of the process of formation of reflexive skills among future managers in the system of secondary vocational education and to analyze the results of experimental work on the implementation of the developed organizational and pedagogical conditions in the educational process. Review of the scientific literature on the problem. The analysis and synthesis of professional and educational standards, normative legal documents of secondary vocational education is carried out. The analysis of scientific works of philosophers who have studied human reflection and thinking is carried out. The works on psychology devoted to the problem of understanding the essence of the process of reflection and the formation of reflexive competence of the individual’s personality in modern society are considered. In the field of pedagogical science and practice, the analysis of scientific works devoted to the competence approach and the study of the essence of the process of forming reflexive skills is carried out. The elements of the methodology of pedagogy and the theory of pedagogical research are systematized, in particular, the concept of humanization of the educational process, the methodology of personality-oriented learning, the competence approach, the theory of reflexive activity, on the basis of which systematization of an educational process is carried out within the framework of modern tendencies and trends. Methodology (materials and methods). Based on the research of scientific works of Russian and foreign authors devoted to the development of pedagogical theory and practice in the field of vocational education and arrangement of an educational process in vocational education institutions. The analysis and synthesis of practical methods and techniques that contribute to systematization of the process of formation of reflexive skills among future managers in the Secondary Professional Education (SPE) system is carried out. The analysis of scientific literature, a survey among teachers and heads of institutions in the SPE system, allowed us to identify and justify the features of the formation of reflexive skills among future managers in the SPE system and to develop organizational conditions for the process of developing these skills. The article shows the content, features, and results of the implementation of these conditions. Research results. The article deals with current methods and techniques that provide effective professional training of management students in the system of secondary vocational education, who are able to detect and formulate professional tasks and find ways to solve them. On the basis of the philosophical understanding of reflection, the content of reflexive skills aimed at discovering meanings in their own activities and in the “teacher – student” interaction is determined. The conditions for the formation of reflexive skills in the pedagogical process are revealed: creation and implementation of the typology of reflexive tasks; creation of a dialogic context in educational activities based on construction of the process of solving educational tasks; ensuring personal acceptance of the subject of a reflexive task; filling an educational process with a reflexive component; creation and implementation of the mechanism for development of reflexive skills among future managers in the SPE system. The results of the formation of reflexive skills in the system of secondary vocational education are presented. Conclusion. As a result of the conducted research, the organizational and pedagogical conditions for the formation of reflexive skills among future managers in the SPE system were developed providing a qualitative increase in the level of formation of reflexive skills among students. Consequently, the reconstruction of the educational process in the SPE system, based on the implementation of the presented organizational and pedagogical conditions, significantly optimizes the process of forming the reflexive skills among future managers.

Strengthening Teacher–Student Rapport Through the Practice of Guided Dialogue Journaling

Dialogue journals are written conversations in which two partners communicate regularly. When practiced between a teacher and student, dialogue journaling has the potential to engage students in writing, and can lead to improved teacher–student rapport. In this Innovations in Practice article, we evaluate the use of structured dialogue journals between a student teacher and his English as a Second Language (ESL) students during a seven-week teaching practicum at a local secondary school in Hong Kong. The aim of this practice was for the teacher to engage with students on a personal level, thereby enhancing teacher–student rapport – an otherwise challenging goal during short-term school placements. The dialogue journals were designed to elicit students’ learning experiences, other out-of-class life experiences, and personal interests, which, when reciprocated with teachers’ comments, created a dialogic context for improving open and honest teacher–student communication in English. In this practice, a total of 11 rounds of dialogue journals were administered and completed throughout the teaching practicum period. An evaluation of the practice was based on an analysis of the dialogue journal entries, semi-structured interviews with students, and the student teacher's own reflection. Implications of this practice are discussed in terms of the possibilities for ESL/English as a Foreign Language (EFL) teachers to use dialogue journals for enhancing teacher–student rapport.

Topic-level knowledge sub-graphs for multi-turn dialogue generation

Previous multi-turn dialogue approaches based on global Knowledge Graphs (KGs) still suffer from generic, uncontrollable, and incoherent responses generation. Most of them neither consider the local topic-level semantic information of KGs nor effectively merge the information of long dialogue contexts and KGs into the dialogue generation. To tackle these issues, we propose a Topic-level Knowledge-aware Dialogue Generation model to capture context-aware topic-level knowledge information. Our method thus accounts for topic-coherence, fluency, and diversity of generated responses. Specifically, we first decompose the given KG into a set of topic-level sub-graphs, with each sub-graph capturing a semantic component of the input KG. Furthermore, we design a Topic-level Sub-graphs Attention Network to calculate the comprehensive representation of both sub-graphs and previous turns of dialogue utterances, which then decoded with the current turn into a response. By using sub-graphs, our model is able to attend to different topical components of the KG and enhance the topic-coherence. We perform extensive experiments on two datasets of DuRecDial and KdConv to demonstrate the effectiveness of our model. The experimental results demonstrate that our model outperforms existing strong baselines.

The system of interaction between the state and the citizen in Uzbekistan: renewal and development paths

The article is devoted to the analysis of some theoretical and practical aspects of such a phenomenon as the system of interaction between the state and the citizen in the Republic of Uzbekistan, as well as the consideration of the place of legal values in this system, the grounds and conditions for the establishment of e-democracy, the importance of administrative procedures and public services. The characteristic of the basic legal values of the system of interaction between the state and citizens is given, the position is argued according to which constitutional values determine the essence of the relationship between them. E-democracy is considered in the context of the process of increasing the participation of citizens in the democratic management of state affairs, ensuring the transparency of the activities of state bodies, as well as their interaction with the population. The authors notes that the elements of e-democracy are most visibly manifested in the practice of interaction between the state and society. Given the assessment of the state of development of e-democracy in the country, the authors made an attempt to consider the prospects for its further development in Uzbekistan. Administrative procedures and public services are considered as instruments of interaction between the state and the population, in the context of dialogue between the state and the citizen.

Is it a good move? Mining effective tutoring strategies from human–human tutorial dialogues

To construct dialogue-based Intelligent Tutoring Systems (ITS) with sufficient pedagogical expertise, a trendy research method is to mine large-scale data collected by existing dialogue-based ITS or generated between human tutors and students to discover effective tutoring strategies. However, most of the existing research has mainly focused on the analysis of successful tutorial dialogue. We argue that, to better inform the design of dialogue-based ITS, it is also important to analyse unsuccessful tutorial dialogues and gain a better understanding of the reasons behind those failures. Therefore, our study aimed to identify effective tutoring strategies by mining a large-scale dataset of both successful and unsuccessful human–human online tutorial dialogues, and further used these tutoring strategies for predicting students’ problem-solving performance. Specifically, the study adopted a widely-used educational dialogue act scheme to describe the action behind utterances made by a tutor/student in the broader context of a tutorial dialogue (e.g., asking/answering a question, providing hints). Frequent dialogue acts were identified and analysed by taking into account the prior progress that a student had made before the start of a tutorial session and the problem-solving performance the student achieved after the end of the session. Besides, we performed a sequence analysis on the inferred actions to identify prominent patterns that were closely related to students’ problem-solving performance. These prominent patterns could shed light on the frequent strategies used by tutors. Lastly, we measured the power of these tutorial actions in predicting students’ problem-solving performance by applying a well-established machine learning method, Gradient Tree Boosting (GTB). Through extensive analysis and evaluations, we identified a set of different action patterns that were pertinent to tutors and students across dialogues of different traits, e.g., students without prior progress in solving problems, compared to those with prior progress, were likely to receive more thought-provoking questions from their tutors. More importantly, we demonstrated that the actions taken by students and tutors during a tutorial process could not adequately predict student performance and should be considered together with other relevant factors (e.g., the informativeness of the utterances).