Model-based analysis of thinking in problem posing as sentence integration focused on violation of the constraints.

The advancement of computer and communication technologies has enabled researchers to conduct and analyze the learning process of posing problems. This study investigates what learners think while posing problems as sentence integration in terms of intermediate products as well as the posed problems as the resultant product. Problem posing as sentence integration defines the arithmetic word problem structure, and posing a problem is a task to satisfy all the constraints and requirements to build a valid structure. A previous study shows that, in problem posing as sentence integration for arithmetic word problems, learners try to satisfy a relatively large number of constraints in the posed problems. In contrast, this study focuses on the violation of constraints in the intermediate products while posing problems. The result shows that learners were inclined to avoid as many violated constraints as possible throughout the problem-posing process. Although learners tend to avoid the violated constraints, naturally, they cannot avoid some mistakes. Further analysis shows that learners actually have difficulty in fulfilling particular constraints while posing the problems. Based on this analysis, it is possible to detect the difficulty of learners' actions from the model perspective. Hence, it is possible to give accurate feedback and appropriately support the learners.

The practical use of Kit-Build concept map on formative assessment.

Formative assessment can encourage an instructor to improve learning achievements in a lecture class. The goal of formative assessment in a classroom situation is monitoring learners to provide instructor's feedback for improving learner's understanding as well as instructor's expectation. A Kit-Build concept map is a digital tool for supporting a concept map strategy to represent instructor's expectation and to assess the current understanding of learners. The Kit-Build concept map is also adequate for implementing the formative assessment in a lecture class. The proposition level exact matching between the concept map of instructor and learners can generate the diagnosis results for informing the instructor about the gaps between current learner's understanding and the instructor's expectation. Accordingly, the instructor can design the feedback based on the diagnosis results for improving the understanding of learners. In this paper, we propose the arrangement of the ability of the Kit-Build concept map on formative assessment in a lecture class for creating an opportunity to assess current understanding of learners as more as possible. And we present the effectiveness of the Kit-Build concept map on the closed-end approach in elementary school through three practical uses in various lecture classes, which illustrate the contribution of the Kit-Build concept map when utilized on formative assessment in the lecture class.

An analysis of learner outputs in problem posing as sentence-integration in arithmetic word problems.

Achieving practical implementation of learning by problem posing faces the issue of inefficiency due to the time needed for assessment and giving feedback to students' posed problems. As a solution of this problem, we have developed a tablet PC-based software for learning by posing arithmetic word problems named Monsakun. The software is based on Triplet Structure Model of arithmetic word problem. In this research, we investigated problems posed by elementary school students in Monsakun to understand whether Monsakun encourages them to think about the structure of arithmetic word problems. The result shows that students did not pose problems randomly but considered things first. We also found that the frequent errors are actually meaningful errors, and students tried to pose problems satisfying as many constraints as possible, which means they actually think about the structure to pose required problems in the assignments. The process of understanding assignment requirements and relating them to suitable sentence cards is an important point especially for young learners to reach deep understanding of the structure of arithmetic word problems.

Visualizations of problem-posing activity sequences toward modeling the thinking process.

Problem-posing is well known as an effective activity to learn problem-solving methods. Although the activity is considered in contributing to the understanding of the problem's structure, it is not clear how learners could understand it through the activity. This study proposes a method to offer a visual representation for analyzing the problem-posing activity sequence in MONSAKUN, a digital learning environment for problem-posing of arithmetic word problems via sentence integration. This system requires users to pose a problem through combinations of given simple sentences based on the requirement. The system writes every single action into logs as sequences of problem-posing activity. The sequences are considered to represent the thinking processes of learners. The thinking process reflects their understanding and misunderstanding about the structure of the problems. This study created visualizations of learners' problem-posing processes from the data obtained through the practical use of MONSAKUN, including the states in which many learners had difficulties finding the correct answer. In this study, we refer to such states as "trap states." In MONSAKUN, a trap state is a combination of simple sentences where many learners tend to make and need relatively more actions to obtain the correct answer. As the result of the visualization and analysis of the data, some trap states have been identified, and they changed for each trial in the same problem.

A framework of generating explanation for conceptual understanding based on "semantics of constraints".

In science education, conventional problem practice hardly helps students reach "conceptual understanding" with which they can solve various problems by making appropriate models of target systems. Students often superficially read the solution of a problem and apply it wrongly to others without understanding the model. It is difficult to teach how to make appropriate models because model-making expertise includes a lot of implicit knowledge. In this paper, we propose a general framework for systematically describing such knowledge, which makes it possible not only to explain various models and the difference between them but also to design/sequence a set of problems appropriate for promoting conceptual understanding. Our framework was proved useful through a preliminary experiment in which the explanations generated based on our framework promoted subjects' (15 graduates and undergraduates) conceptual understanding in mechanics. The framework can be the basis for designing intelligent tutoring systems which explicitly help students reach conceptual understanding.

A generating technique and knowledge representation of multiple-answer problems for learning with solving knowledge.

BACKGROUND: Erroneous answers in multiple-answer problems not only make the correct answer harder to determine but also indicate why the correct choice is suitable and the erroneous one a mistake when compared to the correct answer. However, it is insufficient to simply create erroneous answers for this purpose: explanations of these answers are also required. Preexisting studies examining functions for generating erroneous answers and their explanations based on this approach are abundant. Nevertheless, a major bottleneck has formed in this research body concerning the related specialized knowledge descriptions that are required for the generation function. METHODS: This paper focuses on the notion that it is easy for teachers skilled in problem solving to express specific problems in written form and amend incomplete knowledge. Furthermore, it examines a method of constructing knowledge while generating and updating knowledge from specific problems. RESULT AND CONCLUSION: The suitability of the proposed method was verified by examining actual knowledge constructed by the research subjects.

Framework of kit-build concept map for automatic diagnosis and its preliminary use.

In this paper, we propose a framework of Kit-Build Concept Map (we call it as KB map) where a concept map made by a learner can be diagnosed automatically. In this research, we have divided the task to make a concept map into two sub-tasks: (1) "segmentation task" where parts of the concept map (nodes and links) are extracted from learning resources and (2) "structuring task" where the extracted parts are integrated into a map. In the framework of kit-build concept map, a learner is given a set of parts of a concept map and then re-builds the concept map by combining the given parts. In this process, the segmentation task becomes a task of recognition of the given parts and the structuring task remains as it is. The concept map should be prepared beforehand by a teacher or domain expert. We call this map "goal map." The necessary and sufficient parts (kit) are generated by decomposing the goal map. The parts are provided to learners, and then the learners are required to build concept maps (learner maps) by connecting the parts. Since the same parts are used both in the goal map and a learner map, it is possible to find defects in the learner map as the differences from the goal map. By overlaying several learners' maps, then, a group map can be generated. By comparing the group map with the goal map, differences between the goal map and the group of the learners are detected. We have also realized procedure to re-examine the goal map based on the differences between the group map and the goal map. We have already developed a system that realized the framework of the KB map. Through a preliminary use of the system, we have confirmed that the system works along with the framework of KB map. Evaluation of learning effect is our future work.

Two genomic regions of chromosomes 1 and 18 explain most of the stroke susceptibility under salt loading in stroke-prone spontaneously hypertensive rat/Izm.

To clarify the genetic mechanisms of stroke susceptibility in the stroke-prone spontaneously hypertensive rat (SHRSP), a quantitative trait locus (QTL) analysis was performed. Using 295 F2 rats of a cross between SHRSP/Izm and SHR/Izm, 2 major QTLs for stroke latency under salt loading were identified on chromosomes (chr) 1 and 18. Evaluation of 6 reciprocal single and double congenic rats for these QTLs showed that substitution of the SHRSP for the SHR fragment at the chr 1 and 18 QTLs increased the relative risk for stroke by 8.4 and 5.0, respectively. The combined effect of the 2 QTLs was 10× greater than that of the background genome (by Cox hazard model). Blood pressure monitoring by radio telemetry indicated that the combination of the 2 QTLs had a clear effect on the salt-dependent blood pressure increase, suggesting an important role for the salt-sensitive blood pressure increase in the susceptibility of SHRSP to stroke. A haplotype analysis of 11 substrains of SHRSP and SHR using 340 simple sequence repeat markers in the chr 1 QTL suggested that the 7-Mbp fragment between D1Rat260 and D1Rat178 was most likely to harbor the responsible gene(s), which was confirmed by a study of additional subcongenic strains. This study indicated a major role for 2 QTLs on chr 1 and 18 in stroke susceptibility in SHRSP under salt loading. The salt-sensitive blood pressure increase was implied to play a key role in the stroke susceptibility.

Identification of the transgenic integration site in immunodeficient tgε26 human CD3ε transgenic mice.

A strain of human CD3ε transgenic mice, tgε26, exhibits severe immunodeficiency associated with early arrest of T cell development. Complete loss of T cells is observed in homozygous tgε26 mice, but not in heterozygotes, suggesting that genomic disruption due to transgenic integration may contribute to the arrest of T cell development. Here we report the identification of the transgenic integration site in tgε26 mice. We found that multiple copies of the human CD3ε transgene are inserted between the Sstr5 and Metrn loci on chromosome 17, and that this is accompanied by duplication of the neighboring genomic region spanning 323 kb. However, none of the genes in this region were abrogated. These results suggest that the severe immunodeficiency seen in tgε26 mice is not due to gene disruption resulting from transgenic integration.

The novel tetratricopeptide repeat domain 7 mutation, Ttc7fsn-Jic, with deletion of the TPR-2B repeat causes severe flaky skin phenotype.

We carried out molecular analyses of the novel flaky skin mutation, Ttc7(fsn-Jic )(a synonym for fsn(Jic)), which we found in a previous study. It was revealed that this mutation involved a genomic in-frame deletion including exons 9 and 10 of the Ttc7 gene, and that the genomic deletion in Ttc7 (fsn-Jic )may disrupt the tetratricopeptide repeat-2B domain of the TTC7 protein. Based on a comparison of three Ttc7 mutations, including Ttc7(fsn-J )(a synonym for fsn) and Ttc7(fsn-hea )(a synonym for hea), it was suggested that either exon 9 or exon 10 or both may play a more important role than the other exons of the Ttc7 gene. Ttc7 gene expression analyses using Northern blotting revealed that Ttc7 mRNA is expressed in 11 tissues, except muscle. In conclusion, we confirmed that the Ttc7 (fsn-Jic )mutation, as well as the Ttc7(fsn-J )and Ttc7 (fsn-hea )mutations, is responsible for abnormal phenotypes observed in various tissues of mice with the flaky skin mutation.

Pathogenesis of obesity by food restriction in OLETF rats-increased intestinal monoacylglycerol acyltransferase activities may be a crucial factor.

UNLABELLED: Obesity was considered to be one of the causes of non-insulin-dependent diabetes mellitus (NIDDM). However, the mechanism responsible for obesity has not yet been fully elucidated. In this study, we first examined the relationship between food intake amount and obesity in a NIDDM model animal, and then we focused on triacylglycerol (TG) synthetase activity, which play important roles in hypertriglyceridemia (HTG) associated with obesity. Otsuka Long-Evans Tokushima Fatty (OLETF) rat is an animal model of NIDDM, characterized by obesity, HTG and insulin resistance. In this study, OLETF rats were allocated to a food-satiated group (satiated) or food-restricted group (to eliminate the effects of hyperphagia on obesity, amount of daily food intake was the same as that in their control strain Long-Evans Tokushima Otsuka (LETO) rats). Changes in body weight, body fat, intraabdominal fat weight, and TG content in liver were measured and biochemical blood tests and activity assay of TG synthetase (monoacylglycerol acyltransferase (MGAT) and diacylglycerol acyltransferase (DGAT)) were performed. RESULTS: (1) The body weight in the restricted OLETF rats was significantly decreased to 71.7% of that in the satiated OLETF rats, which was almost the same value as that in the LETO rats. However, body fat and intraabdominal fat weight were significantly increased in restricted OLETF rats and satiated OLETF rats compared with LETO rats. (2) Plasma TG, insulin, glucose, leptin and hepatic TG content were significantly higher in OLETF rats than the values in LETO rats. (3) MGAT activity in the small intestine from both satiated and restricted OLETF rats was significantly higher than that in LETO rats. DGAT activity in OLETF rats was not significantly different from that in LETO rats. In conclusion, the body fat weight and plasma TG were still significantly accelerated in OLETF rats at the same food intake as LETO rats. MGAT activity in the small intestine from OLETF rats was also significantly higher than those of LETO rats. Therefore, high MGAT activity in the small intestine may play an important role in HTG and obesity, subsequently hastening the development of NIDDM in OLETF rats.