Search results for "TASK"
showing 10 items of 1658 documents
Situational expectancies and task values: Associations with students' effort
2017
Abstract According to expectancy-value theory, expectancies and task values are precursors for investing effort into learning. To date, it remains largely unknown (1) to what extent expectancies and values change from one learning situation to another and (2) to what extent inter-individual findings reflect intra-individual motivational processes. We applied an intensive longitudinal design in a sample of 155 pre-service teacher students attending a lecture. Across ten lessons with varying topics, students reported three times per lesson on their situational effort, expectancies, task values (intrinsic, attainment, utility), and cost. We used multilevel structural equation modeling with lea…
The role of study engagement in university students' daily experiences: A multilevel test of moderation
2019
The present study investigated the dynamic nature of students' daily experiences and general study engagement using intra-individual assessment. More specifically, we examined individual differences in the relationship between university students' task-specific value and situational emotions and, further, whether first-year study engagement would moderate this association during the first two years of studies. Intra-individual state assessments were conducted via mobile phone-based experience sampling method (ESM) during participants' first (N = 72) and second (N = 56) academic years, resulting in 3089 and 2912 fully completed state questionnaires. In both years, students were asked five ti…
Individual differences for self-regulating task-oriented reading activities.
2010
The goal of this study is to analyze the self-regulation processes present in task-oriented reading activities. In the 1st experiment, we examined the following self-regulation processes in the context of answering questions about an available text: (a) monitoring the comprehension of the question, (b) self-regulating the search process, and (c) monitoring the decision to search. Skilled and less skilled comprehenders from 7th and 8th grades read 2 texts and answered 16 questions while all their actions were recorded on a computer. We hypothesized that skilled comprehenders would differ from less skilled comprehenders on the 1st 2 processes on the basis of their general comprehension skills…
Evaluating the impact of friends in predicting user’s availability in online social networks
2017
In recent years, Online Social Networks (OSNs) have changed the way people connect and interact with each other. Indeed, most people have registered an account on some popular OSNs (such as Facebook, or Google+) which is used to access the system at different times of the days, depending on their life and habits. In this context, understanding how users connect to the OSNs is of paramount importance for both the protection of their privacy and the OSN’s provider (or third-party applications) that want to exploit this information. In this paper, we study the task of predicting the availability status (online/offline) of the OSNs’ users by exploiting the availability information of their frie…
Entity Recommendation for Everyday Digital Tasks
2021
| openaire: EC/H2020/826266/EU//CO-ADAPT Recommender systems can support everyday digital tasks by retrieving and recommending useful information contextually. This is becoming increasingly relevant in services and operating systems. Previous research often focuses on specific recommendation tasks with data captured from interactions with an individual application. The quality of recommendations is also often evaluated addressing only computational measures of accuracy, without investigating the usefulness of recommendations in realistic tasks. The aim of this work is to synthesize the research in this area through a novel approach by (1) demonstrating comprehensive digital activity monitor…
A low-cost embedded IDS to monitor and prevent Man-in-the-Middle attacks on wired LAN environments
2007
A man-in-the-middle (MitM) attack is, in the scope of a LAN, a technique where an attacker is able to redirect all traffic between two hosts of that same LAN for packet sniffing or data manipulation, without the end hosts being aware of it. Usually these attacks exploit security flaws in the implementation of the ARP protocol at hosts. Up to now, detecting such attacks required setting up a machine with special-purpose software for this task. As an additional problem, few intrusion detection systems (IDS) are able to prevent MitM attacks. In this work we present a low-cost embedded IDS which, when plugged into a switch or hub, is able to detect and/or prevent MitM attacks automatically and …
HUMAN: Hierarchical Universal Modular ANnotator
2020
A lot of real-world phenomena are complex and cannot be captured by single task annotations. This causes a need for subsequent annotations, with interdependent questions and answers describing the nature of the subject at hand. Even in the case a phenomenon is easily captured by a single task, the high specialisation of most annotation tools can result in having to switch to another tool if the task only slightly changes. We introduce HUMAN, a novel web-based annotation tool that addresses the above problems by a) covering a variety of annotation tasks on both textual and image data, and b) the usage of an internal deterministic state machine, allowing the researcher to chain different anno…
Adaptive Task Assignment in Online Learning Environments
2016
With the increasing popularity of online learning, intelligent tutoring systems are regaining increased attention. In this paper, we introduce adaptive algorithms for personalized assignment of learning tasks to student so that to improve his performance in online learning environments. As main contribution of this paper, we propose a a novel Skill-Based Task Selector (SBTS) algorithm which is able to approximate a student's skill level based on his performance and consequently suggest adequate assignments. The SBTS is inspired by the class of multi-armed bandit algorithms. However, in contrast to standard multi-armed bandit approaches, the SBTS aims at acquiring two criteria related to stu…
ASR performance prediction on unseen broadcast programs using convolutional neural networks
2018
In this paper, we address a relatively new task: prediction of ASR performance on unseen broadcast programs. We first propose an heterogenous French corpus dedicated to this task. Two prediction approaches are compared: a state-of-the-art performance prediction based on regression (engineered features) and a new strategy based on convolutional neural networks (learnt features). We particularly focus on the combination of both textual (ASR transcription) and signal inputs. While the joint use of textual and signal features did not work for the regression baseline, the combination of inputs for CNNs leads to the best WER prediction performance. We also show that our CNN prediction remarkably …
Investigating label suggestions for opinion mining in German Covid-19 social media
2021
This work investigates the use of interactively updated label suggestions to improve upon the efficiency of gathering annotations on the task of opinion mining in German Covid-19 social media data. We develop guidelines to conduct a controlled annotation study with social science students and find that suggestions from a model trained on a small, expert-annotated dataset already lead to a substantial improvement - in terms of inter-annotator agreement(+.14 Fleiss' $\kappa$) and annotation quality - compared to students that do not receive any label suggestions. We further find that label suggestions from interactively trained models do not lead to an improvement over suggestions from a stat…