AI Reading Comprehension Assistants Integrating Visual Data for Enhanced Human Understanding

The study investigated teachers’ knowledge of reading comprehension processes and reading comprehension instruction. The study was carried out among teachers (N = 65) in Estonia. The content analysis classified qualitative data from semi-structured interviews as quantitative data. The results showed that teachers’ content knowledge about reading comprehension processes and pedagogical knowledge of reading comprehension instruction were considerably variable yet mostly limited. Special education teachers (n = 37) mentioned a wider range of reading strategies than classroom teachers (n = 28). When describing how to support struggling readers, significant differences emerged between the teacher groups: Special education teachers mentioned activities to support students’ reading comprehension more frequently than classroom teachers whereas classroom teachers mentioned activities for supporting reading motivation more often than special education teachers. Teachers’ lack of knowledge about reading comprehension processes and reading comprehension instruction indicate the need to improve these topics in preservice and in-service teacher training to enhance their teaching skills.

Reading comprehension is a complex process that requires using many skills together. To increase the quality of this process, many strategies, methods, and techniques are applied, and the operability of the applications is the subject of research. When the studies are investigated, it is seen that the effects of strategies, methods, and techniques on students' reading comprehension skills have been examined many times. However, it is not possible to deal with the reading comprehension process only with strategy effectiveness. When the studies conducted at the international and national levels are examined, it is seen that the studies in which primary school students describe their own mental processes in the reading comprehension process are limited. Therefore, this research, it is aimed to examine which strategies, methods and techniques are used by primary school 4th grade students to understand a text they read. The study was carried out with 25 primary school students studying in two public primary schools in Ardahan city center in the 2020-2021 academic year. The case study model, one of the qualitative research designs, was used in the study. A data collection tool, a semi-structured interview form consisting of open-ended questions was used to determine the methods and techniques used by primary school 4th grade students in the reading comprehension process. While preparing the interview form, first, the relevant literature was reviewed and items were created in order to reveal the activities performed by the students before, during and after reading. The semi-structured interview form consisting of 5 open-ended questions was finalized by consulting the expert opinion for the items created. The data obtained in the study were analyzed by the content analysis method. Acording to the results of the research, it was seen that primary school students most frequently used the methods of examining text images, visualizing what they read, summarizing the text, finding the message the author wanted to convey, and mapping the story in the process of reading comprehension.

While introducing reading comprehension activities into the CLIL classroom, it should be remembered that reading comprehension is goal-oriented and may be defined as searching for meaning and sense. In the CLIL classroom, this goal is not only to develop reading comprehension skills or search for meaning of particular words but also to expand content knowledge. Secondly, reading comprehension is the act of comprehension. Comprehension is a highly active constructive process, and it is here that the key to language learning as well as content learning lie. Finally, the process of reading comprehension is dynamic and strategic. In other words, the best idea is to introduce techniques and activities which will not be boring for the learners and which will require the use of various metacognitve strategies. The term “metacognitive awareness” is conceptualized as the ‘knowledge of the readers’ cognition relative to the reading process and the self-control mechanism they use to monitor and enhance comprehension” (Sheorey and Mokhtari 2001, p. 423), which is a critical component of skilled reading. The purpose of my study was to explore the role of metacognitive strategies in L2 reading comprehension. The participants were University students who learn content subjects in English and were asked take reading comprehensions test and to fill in metacognitive reading strategies questionnaire. The intention of this address is to discuss different metacognitive reading strategies used by the CLIL University learners.

Human-computer interaction for virtual-real fusion

Much research in robotic artificial intelligence (AI) and Artificial Life has focused on autonomous agents as an embodied and situated approach to AI. Such systems are commonly viewed as overcoming many of the philosophical problems associated with traditional computationalist AI and cognitive science, such as the grounding problem (Harnad) or the lack of intentionality (Searle), because they have the physical and sensorimotor grounding that traditional AI was argued to lack. Robot lawn mowers and self-driving cars, for example, more or less reliably avoid obstacles, approach charging stations, and so on-and therefore might be considered to have some form of artificial intentionality or intentional directedness. It should be noted, though, that the fact that robots share physical environments with people does not necessarily mean that they are situated in the same perceptual and social world as humans. For people encountering socially interactive systems, such as social robots or automated vehicles, this poses the nontrivial challenge to interpret them as intentional agents to understand and anticipate their behavior but also to keep in mind that the intentionality of artificial bodies is fundamentally different from their natural counterparts. This requires, on one hand, a "suspension of disbelief " but, on the other hand, also a capacity for the "suspension of belief." This dual nature of (attributed) artificial intentionality has been addressed only rather superficially in embodied AI and social robotics research. It is therefore argued that Bourgine and Varela's notion of Artificial Life as the practice of autonomous systems needs to be complemented with a practice of socially interactive autonomous systems, guided by a better understanding of the differences between artificial and biological bodies and their implications in the context of social interactions between people and technology.

Artificial Intelligence in the American Healthcare Industry: Looking Forward to 2030

Evidence for Top-Down Processing in Reading Comprehension of Children

According to The Simple View of Reading, both decoding and linguistic comprehension processes are needed for reading comprehension for L1 as well as L2 students. Previous research has shown that early support is important for students who struggle with reading. The thesis aims to investigate the role of decoding and comprehension for students learning to read in Swedish as L2 and how teaching and early special support can promote reading development. The first study in the thesis has a cross-sectional design and examines scores on decoding, vocabulary, and reading comprehension. The results showed that L2 students in grades 1-3 in Sweden had significantly weaker scores on all three tests than L1 students and that both decoding and vocabulary are related to reading comprehension. The results also showed that a significantly higher proprtion of L2 students were in need of extra support in reading. The second study is a systematic scoping review that identifies findings from reading intervention studies of L2 students. The results showed that additional small group or within-class programs can support L2 students when teaching is matched to their individual needs. The study also supported the view that instruction in skills in one language can transfer to skills in another. The third study has a between-groups design and investigates the impact of a Response to Intervention (RTI) model with a focus on decoding. The results showed that the RTI model had the potential to promote both L1 and L2 student's reading ability but to a lesser extent among L2 students. The forth study has a single subject design and examines the impact of a systematic word decoding intervention in Swedish for students learning Swedish as L2. All students improved their word decoding ability. In conclusion, it can be seen that differentiated balanced reading instruction and early support in an inclusive setting can promote reading ability in students learning Swedish as a second language. A second language perspective in early reading education is discussed.

Introduction: Working memory and reading comprehension are essential cognitive processes for students academic development. Objective: This research explores the relationship between these variables in elementary school children, analyzing key studies that demonstrate how working memory facilitates decoding and text processing and on the other hand, in reading comprehension, as a process of great importance in meaningful learning, interpretation and consolidation of a priori knowledge in children. Methodology: Theoretical models such as Baddeley and Hitch (1974) are discussed and their applicability in the educational context is evaluated. Result: The implications of these findings are highlighted to design pedagogical strategies that optimize more effective teaching strategies based on the needs and abilities of the students, which can help to improve their skills in the reading comprehension process. Conclusion: Finally, it was possible to identify gaps in the literature that may help future research proposals that can generate pedagogical interventions based on these skills to optimize academic performance.

The purpose of this research is to reveal the process of teaching reading comprehension of narrative texts, and to find out the teacher's problems in applying story mapping techniques in teaching reading comprehension of narrative texts. This study uses qualitative research with a case study method. Data was collected from observation, interviews, and documentation. The participant in this study was an English teacher for class X IPA who taught narrative texts by applying the story mapping technique. The process of teaching and learning reading comprehension is going well, although not optimal. Meanwhile, there are five problems faced by the teacher in teaching reading comprehension, namely the teacher has difficulty if students cannot achieve basic mastery in reading, the teacher has difficulty if students read very slowly the reading text being taught, the teacher has difficulty if students cannot understand and find. conclusions, implications, and main ideas of the reading text, the teacher has difficulties in choosing teaching materials in teaching reading comprehension of narrative texts, and the teacher has problems in designing or modifying questions and exercises to attract students' interest in learning reading comprehension of narrative texts.

Both human brain and computer (electronic brain) could process data and do some cognition and computation tasks. Is the cognition of human brain equal to the computation of computer? It is obviously not. In this talk, the relationships of brain cognition models and intelligence computation models are summarized into four different types, that is, human brain cognition inspired intelligence computation (BCIIC), intelligence computation without human brain cognition (ICOBC), intelligence computation assisted human brain cognition (ICABC), and the integration of human brain cognition and intelligence computation (BC&IC). There are three paradigms in traditional artificial intelligence (AI) studies, that is, symbolism AI, connectionism AI, and behaviorism AI. The physical symbol system hypothesis is used in the symbolism AI. Human brain cognition is taken as a kind of symbolic processing, and the processes of human thinking are computed by symbol in the symbolism AI [1,2]. The connectionism AI relies on the bionics to simulate human brain. In the connectionism AI, neuron is taken as the basic unite of human thinking, and the intelligence is taken as the result of interconnected neurons competition and collaboration [3,4]. In the behaviorism AI, intelligence depends on the perception and behavior, “Perception-action” model is used, and intelligence may not require knowledge, knowledge representation and knowledge reasoning [5]. The symbolism AI and connectionism AI are two different types of human brain cognition inspired intelligence computation, while the behaviorism AI is a representative case of intelligence computation without human brain cognition. Usually, AI researchers get some inspiration from human brain cognition in their studies. On the other way, intelligence computation could also assist human brain cognition studies. The bidirectional cognitive computing model (BCC) is such a case. It studies the bidirectional transformations between the intension and extension of a concept. It is used to simulate some human brain cognition tasks such as learning and recognition [6,7]. Cognitive computing is one of the core fields of artificial intelligence [8,9]. Data-driven granular cognitive computing (DGCC) is an example of the integration of human brain cognition and intelligence computation [10,11]. It takes data as a special kind of knowledge expressed in the lowest granularity level of a multiple granularity space. It integrates two contradictory mechanisms, namely, the human’s cognition mechanism of ‘‘global precedence’’ which is a cognition process of ‘‘from coarser to finer’’ and the information processing mechanism of machine learning systems which is ‘‘from finer to coarser’’, in a multiple granularity space. It is data-driven cognitive computing model. The integration of human brain cognition and intelligence computation would be an important research topic of artificial intelligence. Some scientific research issues of the integration of human brain cognition and intelligence computation are discussed based on DGCC.

Dynamics of Reading Comprehension Skills in Linguistic Intervention Programme

Comprehension during reading involves higher‐order processing of discourse structure and the reader's knowledge in interaction with lower‐level word coding processes. The interactions between these “top‐down” and “bottom‐up” processes must be taken into account in models of comprehension. The suggestion made in this paper is that word codingand sentence comprehension processes must execute fast enough to sustain active text memories. It is argued that memory deactivation due to breakdowns in the synchrony of coding and comprehension subcomponents is a major source of individual skill differences in reading comprehension. Four lines of evidence that supports this hypothesis are reviewed: (1) Less skilled readers show slower or less accurate performance on certain verbal processing tasks. (2) Such less skilled readers do not necessarily have deficient general short‐term memory capacity. (3) Normal reading is disrupted by relatively minor interferences with coding processes. (4) The availability of relevant ...

Using Artificial Intelligence for Text Screening in a Systematic Review of Cardiotoxicity

Language learning is an intuitive statistical learning problem…. Research in cognitive psychology demonstrates that such implicit tallying is the raw basis of human pattern recognition, categorization, and rationalcognition. (Ellis, 2007: 80–81) Chapters 2 and 3 provide an outline of how reading comprehension arises out of the efficient combination of lower-level and higher-level processes. The present chapter explores more general cognitive concepts that intersect with reading comprehension. These concepts help explain the effectiveness of various components of reading abilities as they work in combination. This chapter helps explain how fluency and automaticity emerge as incremental outcomes of the implicit learning system, why extensive exposure to print is a crucial goal for reading development (to provide continual implicit learning opportunities and incremental growth of reading abilities), and how reading, and learning from texts, is supported by attentional processing, inferencing, and background knowledge of many types. These concepts and underlying cognitive processing systems are not solely involved in reading-comprehension processing; rather, they are key to all aspects of learning (including all aspects of language learning). Each of the following concepts and cognitive systems is critical for understanding the central role of cognition in reading comprehension: Implicit and explicit learning Frequency, associative learning, co-occurrence, and emergence Attention, noticing, and consciousness Inferencing The role of context in L2 reading The role of background knowledge in L2 reading The importance of these cognitive concepts for reading cannot be overestimated. They constitute the foundations of learning theory for all cognitive and educational psychology. They provide the basis not only for how reading comprehension works, but also for how it develops.