Higher Order Thinking by Setting and Debriefing Tasks in Dutch Geography Lessons

Tasks are a powerful instrument for geography teachers, as they let students engage with the subject. To advance the cumulative learning of students, teachers have to make sure that students learn how to deal with complex and abstract knowledge structures. In the Netherlands, teachers face a dilemma when it comes to task setting: the intended curriculum aims for a considerable part at (parts of) higher order thinking, whereas the high-stakes exams have a clear focus on the use of thinking strategies. This paper explores the task setting and debriefing of Dutch geography teachers by analyzing twenty-three videotaped lessons in upper secondary education by using the Geography Task Categorization Framework. The results show that Dutch teachers mostly rely on textbooks when setting tasks. The focus lies on reproduction and the use of thinking strategies. Tasks aiming at (parts of) higher order thinking are barely used. Furthermore, teachers use tasks from previous high-stakes exams already used in an early stage of upper secondary education. In the debriefing of tasks, teachers move from simple and concrete to complex and abstract knowledge and vice versa. However, most of these movements aim at simplifying knowledge structures. In the observed lessons, curriculum aims at the level of (parts of) higher order thinking are not achieved. The evaluative rules as set by the high-stakes exams and the type of tasks offered by textbooks seem to be dominant.

Limits to the Rational Production of Discourse Connectives

Rational accounts of language use such as the uniform information density hypothesis, which asserts that speakers distribute information uniformly across their utterances, and the rational speech act (RSA) model, which suggests that speakers optimize the formulation of their message by reasoning about what the comprehender would understand, have been hypothesized to account for a wide range of language use phenomena. We here specifically focus on the production of discourse connectives. While there is some prior work indicating that discourse connective production may be governed by RSA, that work uses a strongly gamified experimental setting. In this study, we aim to explore whether speakers reason about the interpretation of their conversational partner also in more realistic settings. We thereby systematically vary the task setup to tease apart effects of task instructions and effects of the speaker explicitly seeing the interpretation alternatives for the listener. Our results show that the RSA-predicted effect of connective choice based on reasoning about the listener is only found in the original setting where explicit interpretation alternatives of the listener are available for the speaker. The effect disappears when the speaker has to reason about listener interpretations. We furthermore find that rational effects are amplified by the gamified task setting, indicating that meta-reasoning about the specific task may play an important role and potentially limit the generalizability of the found effects to more naturalistic every-day language use.

A multi-task approach to argument frame classification at variable granularity levels

Within the field of argument mining, an important task consists in predicting the frame of an argument, that is, making explicit the aspects of a controversial discussion that the argument emphasizes and which narrative it constructs. Many approaches so far have adopted the framing classification proposed by Boydstun et al. [3], consisting of 15 categories that have been mainly designed to capture frames in media coverage of political articles. In addition to being quite coarse-grained, these categories are limited in terms of their coverage of the breadth of discussion topics that people debate. Other approaches have proposed to rely on issue-specific and subjective (argumentation) frames indicated by users via labels in debating portals. These labels are overly specific and do often not generalize across topics. We present an approach to bridge between coarse-grained and issue-specific inventories for classifying argumentation frames and propose a supervised approach to classifying frames of arguments at a variable level of granularity by clustering issue-specific, user-provided labels into frame clusters and predicting the frame cluster that an argument evokes. We demonstrate how the approach supports the prediction of frames for varying numbers of clusters. We combine the two tasks, frame prediction with respect to media frames categories as well as prediction of clusters of user-provided labels, in a multi-task setting, learning a classifier that performs the two tasks. As main result, we show that this multi-task setting improves the classification on the single tasks, the media frames classification by up to +9.9 % accuracy and the cluster prediction by up to +8 % accuracy.

Concurrent visual working memory bias in sequential integration of approximate number

Previous work has shown bidirectional crosstalk between Working Memory (WM) and perception such that the contents of WM can alter concurrent percepts and vice versa. Here, we examine WM-perception interactions in a new task setting. Participants judged the proportion of colored dots in a stream of visual displays while concurrently holding location- and color information in memory. Spatiotemporally resolved psychometrics disclosed a modulation of perceptual sensitivity consistent with a bias of visual spatial attention towards the memorized location. However, this effect was short-lived, suggesting that the visuospatial WM information was rapidly deprioritized during processing of new perceptual information. Independently, we observed robust bidirectional biases of categorical color judgments, in that perceptual decisions and mnemonic reports were attracted to each other. These biases occurred without reductions in overall perceptual sensitivity compared to control conditions without a concurrent WM load. The results conceptually replicate and extend previous findings in visual search and suggest that crosstalk between WM and perception can arise at multiple levels, from sensory-perceptual to decisional processing.

Rule Perseveration during Task-Switching in Brain Tumor: A Severe Form of Task-Setting Impairment

It has been proposed that at least two distinct processes are engaged during task-switching: reconfiguration of the currently relevant task-set and interference resolution arising from the competing task-set. Whereas in healthy individuals the two are difficult to disentangle, their disruption is thought to cause different impairments in brain-damaged patients. Yet, the observed deficits are inconsistent across studies and do not allow drawing conclusions regarding their independence. Forty-one brain tumor patients were tested on a task-switching paradigm. We compared their performance between switch and repeat trials (switch cost) to assess rule reconfiguration, and between trials requiring the same response (congruent) and a different response for the two tasks (incongruent) to assess interference control. In line with previous studies, we found the greatest proportion of errors on incongruent trials, suggesting an interference control impairment. However, a closer look at the distribution of errors between two task rules revealed a rule perseveration impairment: Patients with high error rate on incongruent trials often applied only one task rule throughout the task and less frequently switched to the alternative one. Multivariate lesion-symptom mapping analysis unveiled the relationship between lesions localized in left orbitofrontal and posterior subcortical regions and perseveration scores, measured as absolute difference in accuracy between two task rules. This finding points to a more severe task-setting impairment, not reflected as a mere switching deficit, but instead as a difficulty in creating stable task representations, in line with recent accounts of OFC functions suggesting its critical role in representing task states.

Artificial Intelligence in Medical Imaging and Its Application in Sonography for the Management of Liver Tumor

Recent advancement in artificial intelligence (AI) facilitate the development of AI-powered medical imaging including ultrasonography (US). However, overlooking or misdiagnosis of malignant lesions may result in serious consequences; the introduction of AI to the imaging modalities may be an ideal solution to prevent human error. For the development of AI for medical imaging, it is necessary to understand the characteristics of modalities on the context of task setting, required data sets, suitable AI algorism, and expected performance with clinical impact. Regarding the AI-aided US diagnosis, several attempts have been made to construct an image database and develop an AI-aided diagnosis system in the field of oncology. Regarding the diagnosis of liver tumors using US images, 4- or 5-class classifications, including the discrimination of hepatocellular carcinoma (HCC), metastatic tumors, hemangiomas, liver cysts, and focal nodular hyperplasia, have been reported using AI. Combination of radiomic approach with AI is also becoming a powerful tool for predicting the outcome in patients with HCC after treatment, indicating the potential of AI for applying personalized medical care. However, US images show high heterogeneity because of differences in conditions during the examination, and a variety of imaging parameters may affect the quality of images; such conditions may hamper the development of US-based AI. In this review, we summarized the development of AI in medical images with challenges to task setting, data curation, and focus on the application of AI for the managements of liver tumor, especially for US diagnosis.

Some Time Violations Go Less Noticed: Gestalt Grouping? A Brief Report

This brief report is inspired by Bolton’s (1894, Am. J. Psychol., 6, 145–238) tick-tock phenomenon, which describes an illusionary accented grouping of isochronous, non-accented click sequences. It has repeatedly been shown that in stimulus-wise grouped sequences of an XXXOOO character (where X differs from O in terms of intensity, pitch level, or filled or unfilled duration), gap deviations between groups are more prone to go unnoticed compared to deviations within a group (e.g., Fitzgibbons et al., 1974, Percept. Psychophys., 16, 522–528.). Yet, not much is known about whether comparable anisochrony insensitivities might also occur in equal-accented sequences (XXXXX). In a same/different task setting, listeners had to detect isochrony deviations that appeared in different empty-interval locations across 800 trials within a five-pulse sequence of 250 ms interonset intervals. Findings revealed a major location dependency, with least detection accuracy for gap deviations occurring in the last interval, particularly if the 250 ms gap was lengthened rather than shortened. Results are discussed in relation to potential Gestalt grouping and Nakajima et al.’s (2014, Perception, 33, 1061–1079) perceptual assimilation and contrast observations in three-tone sequences.

Representation of the observer’s predicted outcome value in mirror and nonmirror neurons of macaque F5 ventral premotor cortex

Both the populations of F5 mirror neurons and nonmirror neurons represent the predicted value of an outcome resulting from the observation of a grasping action. Value-dependent motivation, arousal, and attention directed at the observed action do not provide a better explanation for this representation. The population activity’s metric suggests an optimal scaling of value representation to task setting.

Concurrent visual working memory bias in sequential integration of approximate number

Previous work has shown bidirectional crosstalk between Working Memory (WM) and perception such that the contents of WM can alter concurrent percepts and vice versa. Here, we examine WM-perception interactions in a new task setting. Participants judged the proportion of colored dots in a stream of visual displays while concurrently holding location- and color information in memory. Spatiotemporally resolved psychometrics disclosed a modulation of perceptual sensitivity consistent with a bias of visual spatial attention towards the memorized location. However, this effect was short-lived, suggesting that the visuospatial WM information was rapidly deprioritized during processing of new perceptual information. Independently, we observed robust bidirectional biases of categorical color judgments, in that perceptual decisions and mnemonic reports were attracted to each other. These biases occurred without reductions in overall perceptual sensitivity compared to control conditions without a concurrent WM load. The results conceptually replicate and extend previous findings in visual search and suggest that crosstalk between WM and perception can arise at multiple levels, from sensory-perceptual to decisional processing.