Dynamic Assessment Approach Research Articles

Innovative Digital Phenotyping Method to Assess Body Representations in Autistic Adults: A Perspective on Multisensor Evaluation.

In this perspective paper, we propose a novel tech-driven method to evaluate body representations (BRs) in autistic individuals. Our goal is to deepen understanding of this complex condition by gaining continuous and real-time insights through digital phenotyping into the behavior of autistic adults. Our innovative method combines cross-sectional and longitudinal data gathering techniques to investigate and identify digital phenotypes related to BRs in autistic adults, diverging from traditional approaches. We incorporate ecological momentary assessment and time series data to capture the dynamic nature of real-life events for these individuals. Statistical techniques, including multivariate regression, time series analysis, and machine learning algorithms, offer a detailed comprehension of the complex elements that influence BRs. Ethical considerations and participant involvement in the development of this method are emphasized, while challenges, such as varying technological adoption rates and usability concerns, are acknowledged. This innovative method not only introduces a novel vision for evaluating BRs but also shows promise in integrating traditional and dynamic assessment approaches, fostering a more supportive atmosphere for autistic individuals during assessments compared to conventional methods.

AI-Enhanced GraphoText Analysis for Tracking Counselling Therapy Progress: Integrating Multimodal Graphology and Machine Learning

Despite the robustness of existing instruments, routine manual observation in psychotherapy faces significant challenges, including lack of time, labour, high implementation costs, and potential biases such as response bias and social desirability. This study proposes a dynamic assessment approach using machine learning and multimodal features extracted from handwriting, incorporating graphology-based and content-based features. The integration of content-based and graphology-based features involves combining text and handwriting features with the Support Vector Machine (SVM) using the Radial Basis Function Kernel (RBF). The results show that this approach achieves an impressive accuracy rate of 86.25%. The proposed framework not only improves psychotherapeutic practise, but also offers new insights into human cognition and emotional dynamics by revealing intricate patterns in handwriting. This advance facilitates data-driven decision-making, improves the quality of patient care, and overcomes challenges associated with manual monitoring, including social desirability bias and response set bias. This research paves the way for innovative methods at the interface of mental health and technology, and promises a more objective and efficient approach to monitoring the progress of psychotherapy.

The effect of cognitive intervention program on intelligence scores in preschool.

Dynamic assessment is an approach that aims to improve student performance through interventions. One of the important application areas of dynamic assessment is the assessment of intelligence. Within the scope of the study, after a Cognitive intervention program (CIP) was developed, its effects on intelligence scores were examined with a quasi-experimental research method. The CIP was prepared by adopting a dynamic assessment approach to improve the performance of students with expert support. This improvement would be provided by the clues and feedback given during the intervention within the scope of the CIP. The sample of the study included 173 students in the 5-6 age group (83 experimental group, 90 control group). The CIP developed by the researcher consisted of 54 worksheets and was applied to the experimental group for 9weeks. The implementation of the worksheets was supervised by classroom teachers. The digital application of the Anadolu-Sak Intelligence Scale (d-ASIS) and Raven's colored progressive matrices (RCPM) were applied to both the experimental and control groups as pretests and posttests. The increases in the intelligence scores of the experimental and control groups were analyzed by MANOVA. The analysis showed that the intelligence levels of the experimental group increased significantly more than the control group in terms of both d-ASIS and RCPM total gain scores (posttest to pretest). This result indicated that the CIP, which was developed by adopting a dynamic assessment approach, supported cognitive development.

Dynamic assessment approach for intelligent power distribution systems based on runtime verification with requirements updates

The study aims to address the challenge of dynamic assessment in power systems by proposing a design scheme for an intelligent adaptive power distribution system based on runtime verification. The system architecture is built upon cloud–edge-end collaboration, enabling comprehensive monitoring and precise management of the power grid through coordinated efforts across different levels. Specifically, the study employs the adaptive observer approach, allowing dynamic adjustments to observers to reflect updates in requirements and ensure system reliability. This method covers both structural and parametric adjustments to specifications, including updating time protection conditions, updating events, and adding or removing responses. The results demonstrate that with the implementation of adaptive observers, the system becomes more flexible in responding to changes, significantly enhancing its level of efficiency. By employing dynamically changing verification specifications, the system achieves real-time and flexible verification. This research provides technical support for the safe, efficient, and reliable operation of electrical power distribution systems.

Promoting interaction and lowering speaking anxiety in an EMI course: a group dynamic assessment approach

Abstract This study first examined the effectiveness of applying the Group Dynamic Assessment (G-DA) approach to assessing the oral skills of non-native English-speaking university students who are provided with mediation by their teacher in a small group setting. Second, it aimed to understand whether employing innovative G-DA techniques could reduce the speaking anxiety felt by university students if they received support from either their teacher or their peers during assessment. Fifty freshmen’ speaking performance on TOEFL integrated speaking tasks, and their responses to the teacher’s mediation in groups were compared. Results showed that (1) the G-DA approach could be a beneficial tool for assessing English oral proficiency in the EMI context, and (2) the procedures involved in G-DA helped university students feel less anxiety when prompted to respond orally. It provides insights into an alternative approach to assessment which can be employed to group learning in the context of EMI courses.

Approaching the challenge of multi-phase, multi-hazard volcanic impact assessment through the lens of systemic risk: application to Taranaki Mounga

Effective volcanic impact and risk assessment underpins effective volcanic disaster risk management. Yet contemporary volcanic risk assessments face a number of challenges, including delineating hazard and impact sequences, and identifying and quantifying systemic risks. A more holistic approach to impact assessment is required, which incorporates the complex, multi-hazard nature of volcanic eruptions and the dynamic nature of vulnerability before, during and after a volcanic event. Addressing this need requires a multidisciplinary, integrated approach, involving scientists and stakeholders to co-develop decision-support tools that are scientifically credible and operationally relevant to provide a foundation for robust, evidence-based risk reduction decisions. This study presents a dynamic, longitudinal impact assessment framework for multi-phase, multi-hazard volcanic events and applies the framework to interdependent critical infrastructure networks in the Taranaki region of Aotearoa New Zealand, where Taranaki Mounga volcano has a high likelihood of producing a multi-phase explosive eruption within the next 50 years. In the framework, multi-phase scenarios temporally alternate multi-hazard footprints with risk reduction opportunities. Thus, direct and cascading impacts and any risk management actions carry through to the next phase of activity. The framework forms a testbed for more targeted mitigation and response planning and allows the investigation of optimal intervention timing for mitigation strategies during an evolving eruption. Using ‘risk management’ scenarios, we find the timing of mitigation intervention to be crucial in reducing disaster losses associated with volcanic activity. This is particularly apparent in indirect, systemic losses that cascade from direct damage to infrastructure assets. This novel, dynamic impact assessment approach addresses the increasing end-user need for impact-based decision-support tools that inform robust response and resilience planning.

The effects of text-based and audio-based dynamic glosses on L2 vocabulary learning: a dynamic assessment approach

ABSTRACT The present study investigated the effects of text-based and audio-based dynamic glosses on L2 vocabulary learning within a sociocultural approach. Dynamic glosses were operationalised as a set of incrementally ordered prompts, provided during text-based and audio-based interactions that guided the participants to identify the meaning of unknown vocabulary. Fifty-seven EFL learners were assigned to three experimental groups – dynamic text-based, dynamic audio-based and traditional glosses – as well as a control condition. The participants of the two dynamic glossing conditions received dynamic glosses via written ‘chat’ or orally for a number of unknown words while reading a text. In addition to a non-dynamic post-test, a computerised dynamic assessment tool was also designed to investigate learners’ mediated and unmediated knowledge of the target words following the treatment sessions. The results provided evidence for the efficacy of both text-based and audio-based dynamic glosses for L2 vocabulary learning. The analysis of learners’ mediated and unmediated scores calculated by the computerised tool also revealed that the learners’ mediated scores provide valuable information for assessing learners’ vocabulary knowledge. In particular, the findings suggested that text-based dynamic glosses could result in higher mediated scores compared to the audio-based dynamic glosses.

The Use of Dynamic Assessment for Group Learners in the Language Classroom: A Literature Review

The paper reviews the research on the use of Dynamic Assessment (DA) in the language classroom instruction for group learners. DA assesses learners’ abilities in a comprehensive scope of Zone of Proximal Development (ZPD) from one continuum of actual independent performance to the other continuum of potential performance with external support, and DA also sees the external support offered as a driving force of advancing learners’ development within ZPD. With its unique view, DA sheds the new light to the ESL and EFL language teaching and learning, and most DA studies focus on its effectiveness in promoting the development of EFL and ESL learners’ language skills. However, most studies adopt DA in a one-on-one teacher-student model and address DA’s interplay with individuals’ ZPD, which discourages the implementation of DA in the language classrooms with group learners. This paper reviews the existing research on how DA mediates group learners in the language classroom. The review indicates that among the limited research, most studies follow from Group Dynamic Assessment (GDA) and few studies propose alternative DA approaches. All the studies reviewed confirm DA’s effectiveness of promoting group learners’ learning. However, given the dearth of research, it is insufficient to conclude on DA’s mediation of group learners in the language classroom, and more studies are needed.

Can Wood Pellets from Canada’s Boreal Forest Reduce Net Greenhouse Gas Emissions from Energy Generation in the UK?

We present the results of a study on the climate forcing effects of replacing coal for power generation in the United Kingdom (UK) with wood pellets produced in northern Ontario, Canada. Continuous wood pellet production from two biomass sources were considered: fiber from increased harvesting of standing live trees (stemwood scenario) and from harvest residue provided by ongoing harvesting operations (residue scenario). In both scenarios, biomass was collected from harvesting operations in two forest management units (FMUs) with contrasting harvest residue treatments: natural decay of slash piles in the Hearst FMU and slash pile burning in the Kenora FMU. Life cycle emissions associated with wood pellets were assessed for production, transportation, and combustion to replace coal at a hypothetical power generating station in the UK. Greenhouse gas (GHG) emissions and removals in wood pellet and coal scenarios were assessed using two methods: global warming potential (GWP)-based mass balance and dynamic life cycle assessment (LCA) approaches. In the stemwood scenario, climate change mitigation from replacing coal with wood pellets was not achieved within the study timeline (2020–2100). In the residue scenario, immediate climate change mitigation was achieved with fiber sourced from the Kenora FMU where the current practice is to burn slash piles; for the Hearst FMU, where slash is allowed to decompose in the forest, climate change mitigation occurred 11.6 and 3.1 years after biomass collection began, as assessed by the mass balance and dynamic LCA methods, respectively. Factors affecting mitigation potential in the studied scenarios are discussed.

Integrated dynamic risk assessment of buried gas pipeline leakages in urban areas

In urban areas, buried gas pipeline leakages could potentially cause numerous casualties and massive damage. Traditional static analysis and dynamic probability-based quantitative risk assessment (QRA) methods have been widely used in various industries. However, dynamic QRA methods combined with probability and consequence are rarely used to evaluate gas pipelines buried in urban areas. Therefore, an integrated dynamic risk assessment approach was proposed. First, a failure rate calculation of buried gas pipelines was performed, where the corrosion failure rate dependent on time was calculated by integrating the subset simulation method. The relationship between failure probability and failure rate was considered, and a mechanical analysis model considering the corrosion growth model and multiple loads was used. The time-independent failure rates were calculated by the modification factor methods. Next, the overall evolution process from pipeline failures to accidents was proposed, with the accident rates subsequently updated. Then, the consequences of buried gas pipeline accidents corresponding to the accident types in the evolution process were modeled and analyzed. Finally, based on the above research, dynamic calculation and assessment methods for evaluating individual and social risks were established, and an overall application example was provided to demonstrate the capacity of the proposed approach. A reliable and practical theoretical basis and supporting information are provided for the integrity and emergency management of buried gas pipelines in urban areas, considering actual operational conditions.

An Interventionist Dynamic Assessment Approach to College English Writing in China

ABSTRACT This article explores the value of dynamic assessment (DA) for college English writing (CEW), a required course for millions of students in China that typically enrolls 50 students in each class. An interventionist approach to DA, in which mediation and administration are standardized, was selected and supplemented with a construct-descriptor-based rating checklist as a writing assessment before and after an eight-week instruction phase. The DA group received graduated mediation that focused on the constructs and descriptors from the scale, while a control group received holistic corrections. Data were processed through ANOVA and MANCOVA revealing variable development concerning specific constructs but overall significantly greater improvement by the DA group. The results are interpreted according to the degree of change as indicative of the zone of proximal development. The value of the construct-driven scale and associated descriptors through the mediational process are also discussed. It is argued that interventionist DA is equipped to identify the components and processes within a construct, and in so doing offers the possibility of fine-tuning teachers’ and learners’ understanding of problem areas for individuals.

Dynamic Failure Risk Assessment of Wastewater Treatment and Reclamation Plant: An Industrial Case Study

Due to the growing scarcity of water resources, wastewater reuse has become one of the most effective solutions for industrial consumption. However, various factors can detrimentally affect the performance of a wastewater treatment plant (WWTP), which is considered a risk of not fulfilling the effluent requirements. Thus, to ensure the quality of treated wastewater, it is essential to analyze system failure causes and their potential outcomes and mitigation measures through a systematic dynamic risk assessment approach. This work shows how a dynamic Bayesian network (DBN) can be effectively used in this context. Like the conventional Bayesian network (BN), the DBN can capture complex interactions between failure contributory factors. Additionally, it can forecast the upcoming failure likelihood using a prediction inference. This proposed methodology was applied to a WWTP of the Moorchekhort Industrial Complex (MIC), located in the center of Iran. A total of 15 years’ time frame (2016–2030) has been considered in this work. The first six years’ data have been used to develop the DBN model and to identify the crucial risk factors that are further used to reduce the risk in the remaining nine years. The risk increased from 21% to 42% in 2016–2021. Applying the proposed risk mitigation measures can decrease the failure risk from 33% to 9% in 2022–2030. The proposed model showed the capability of the DBN in risk management of a WWTP system which can help WWTPs’ managers and operators achieve better performance for higher reclaimed water quality.

Estimation of the influence of protective behaviour on expected injuries in transport accidents with hazardous materials

The release of hazardous materials due to transport accidents can have major health consequences for bystanders. The number of casualties will partly be determined by their protective behaviour.This study describes a three-step approach to predict health consequences of protective behaviour (for example, hiding or escaping) of bystanders in the first minutes of a transport accident with hazardous material. First, a discrete choice experiment (DCE) was used to predict protective behaviour. Second, a gas dispersion model (SeReMo) was used to estimate the distribution of casualties for different protective behaviours. Third, results of the DCE and SeReMo were combined to estimate the distribution of casualties in the population-at-risk. This approach was applied to a hypothetical marine accident with different hazardous material scenarios on a large waterway in a close vicinity of a beach/quay with bystanders.An important finding of our study was that in general a short reaction time and escaping in cross-wind direction, as protective behaviours, are of vital importance to reduce the number of casualties. A scenario with a short reaction time and a visible cloud towards the beach/quay resulted in a protective behaviour with the largest reduction of casualties.A dynamic risk assessment approach considering that people threatened by hazardous material are not ‘stationary observers’, but will exhibit protective behaviour, and a risk assessment that takes into account empirical information on expected protective behaviour will present a more realistic estimate of the number and severity of casualties when a large transport accident with hazardous materials would occur.

Moving Beyond Single Word Acquisition of Speech Sounds to Connected Speech Development With Dynamic Assessment.

The aim of this study was to document speech sound development across early childhood from a dynamic assessment (DA) perspective that captures a breadth of linguistic environments using the Glaspey Dynamic Assessment of Phonology (Glaspey, 2019), as well as to provide normative data for speech-language pathologists to compare speech skills when making clinical decisions and provide historical context. Targets of English were evaluated via DA for the (a) age of acquisition in single words; (b) continued development through connected speech; (c) early, mid, and late sequence; and (d) differences between single word and connected speech productions. Data were extracted from the reported results of the norming study for the Glaspey Dynamic Assessment of Phonology, which included a representative sample of 880 children ages 3 years to 10;11 (years;months). Comparisons were made with 49 items including multisyllabic words, clusters, and phonemes of English across word positions. Assessment with DA showed that acquisition in single words is nearly complete by age 6 years with a 90% mastery level, and the sequence suggests an Early-13, Mid-16, and Late-14 for items by word position. In connected speech, a wider range of progression is evident from the emergence of sound production at 50%, 75%, and 90% mastery levels with observed changes between ages 3 and 10 years. Given a DA approach across connected linguistic environments, children continue to progress in their development of speech sounds from early childhood well into their school-age years and for some sounds beyond the age of 10 years. DA challenges the language system to better reflect children's developmental progression.

Lockdown lessons learned. Reconceptualising a Sociology of Education module in ITE using a TPACKframework, optimising pedagogy, enhancing student outcomes through the provision of inclusive and accessible opportunities for learning

ABSTRACT The onset of the Covid-19 pandemic in March 2020 forced Higher Education Institutions (HEIs) to quickly reimagine and rethink how lectures and tutorials would continue, how students would be assessed and progressed and how standards would be maintained. This paper focuses on the pedagogical lessons learned from the online pivot in 2020 and how that learning was then harnessed in the 2020–2021 academic year in the reconceptualization and redesign of a Sociology of Education module in one HEI in Ireland. The module was scaffolded by the TPACK framework (Mishra, P., and M. J. Koehler. 2006. “Technological Pedagogical Content Knowledge: A Framework for Teacher Knowledge.” Teachers College Record 108 (6): 1017–1054), which supported dynamic teaching, learning and assessment approach delivered using both synchronous and asynchronous pedagogies. The paper explores levels and types of student engagement, student outputs across both synchronous and asynchronous elements of the module and how the overall module design impacted positively on student outcomes and student engagement. The provision of multiple points of engagement/tasks for students both synchronously and asynchronously ensured an inclusive strengths-based approach where students felt comfortable and confident enough to engage, articulate themselves and contribute to the module.

Dynamic Assessment Training and Mediational Strategies of EFL Student Mediators

Grounded in Vygotsky's sociocultural theory of mind, dynamic assessment (DA) procedures integrate assessment and instruction into one unified activity. Mediation as the core concept of DA is defined as the assistance and the feedback offered by the mediator to the learners while engaging in the process of assessment. This study aimed at addressing the effect of DA training on the meditational moves of student mediators regarding a writing accuracy task in small groups in an EFL classroom. A multiple case study design was used in this study. Five students underwent DA training during which they were exposed to a large classroom DA by a teacher mediator followed by basic theoretical underpinnings of DA as well as mock DA practice and discussion. Data were collected though video records of DA training workshops and Group Dynamic Assessment sessions. Additionally, stimulated recall was used to help student mediators reflect on the interactions. Language-related episodes were used for data analysis. The findings showed that DA training resulted in qualitative and quantitative changes in the meditational moves of student mediators, which calls for incorporating of small group DA as an essential complementary to large classroom DA and learner-centered approaches to teaching and assessment in the EFL classrooms.

Enhancing Students’ Genre Writing Skills in an English for Specific Purposes Class: A Dynamic Assessment Approach

Dynamic assessment integrates the teaching and testing process. Several studies have been conducted to find out the role of dynamic assessment in enhancing students’ writing skills (Alemi, 2015; Amiri & Saberi, 2016; Sadek, 2015; Shresta & Coffin, 2012). However, studies on its implementation in English for Specific Purposes (ESP) settings are limited. This study aimed to find out the effectiveness of dynamic assessment in improving students’ writing skills, especially the genre of descriptive text in an ESP class. A mixed-method design was used. Seventy students in a Library Technician Program at a public university in Indonesia participated in the study. The data were gathered through pretests and posttests. An analysis of T-test scores showed that they were statistically significant, suggesting that the dynamic assessments had a positive influence on students’ abilities in composing texts. Following these tests, an open-ended questionnaire was administered to obtain students’ opinions. The responses from the questionnaire revealed that most students had positive views toward dynamic assessments as it helped them assess their writing skills, find specific vocabulary, and reduce anxiety.

A probabilistic-based model for dynamic predicting pitting corrosion rate of pipeline under stray current interference

Stray current generated from DC rail transit system would lead to severe electrochemical corrosion on buried gas pipeline. Due to significant dynamic characteristics of stray current, the corrosion of gas pipelines may not be discovered in time, especially when the frequency of in-line inspection is low. In view of this, we originally develop a novel dynamic assessment approach for corrosion rate distribution along the gas pipeline subjected to stray current corrosion. In this model, fluctuation of stray current and influencing parameters are involved in measuring the uncertainty of corrosion rate by using Monte Carlo simulation and specific corrosion behavior is also taken into consideration. The results show that, when the gas pipeline is parallel to the subway line, corrosion rate in the middle section of gas pipeline is much higher than the section at both ends.

A dynamic risk assessment approach based on stochastic hybrid system: Application to microbial hazards in food processing

In food processing, it is essential to guarantee the safety of microbial hazards. Microorganisms exist, transit and continuously grow along the food processing with hybrid evolutionary characteristics and uncertainties. Thus, a particular risk assessment is essential to effectively predict and evaluate the risk of microbial hazards in food processing. For such a purpose, we propose a comprehensive dynamic risk assessment approach based on a stochastic hybrid system (SHS). First, we formulate a dynamic evolution of microorganisms in food processing according to the SHS model. Second, we employ a Monte Carlo simulation to obtain the probability density functions of process characteristic information for microorganisms during processing. Additionally, we design a novel risk indicator of “hazard degree” to quantify the potential risks of microorganisms based on this process information. Finally, we present a case study of wheat flour processing to estimate the risk of mixed mildew on the basis of the SHS approach. Experimental results show that the proposed approach is feasible in modeling the hybrid evolution and handling uncertainties in predictions of microbial hazards. This study should prove to be a valuable reference to ensure food safety for risk management and decision-making departments.

Guiding environmental sustainability of emerging bioconversion technology for waste-derived sophorolipid production by adopting a dynamic life cycle assessment (dLCA) approach.

Microbial biosurfactants are surface-active molecules that are naturally produced by a range of microorganisms. They have certain advantages over chemical surfactants, such as lower toxicity, higher biodegradability, anti-tumor, and anti-microbial properties. Sophorolipids (SLs) in particular are one of the most promising biosurfactants, as they hold the largest share of the biosurfactant market. Currently, researchers are developing novel approaches for SL production that utilize renewable feedstocks and advanced separation technologies. However, challenges still exist regarding consumption of materials, enzymes, and electricity, that are primarily fossil based. Researchers lack a clear understanding of the associated environmental impacts. It is imperative to quantify and optimize the environmental impacts associated with this emerging technology very early in its design phase to guide a sustainable scale-up. It is necessary to take a collaborative perspective, wherein life cycle assessment (LCA) experts work with experimentalists, to quantify environmental impacts and provide recommendations for improvements in the novel waste-derived SL production pathways. Studies that have analyzed the environmental sustainability of microbial biosurfactant production are very scarce in literature. Hence, in this work, we explore the possibility of applying LCA to evaluate the environmental sustainability of SL production. A dynamic LCA (dLCA) framework that quantifies the environmental impacts of a process in an iterative manner, is proposed and applied to evaluate SL production. The first traversal of the dLCA was associated with the selection of an optimal feedstock, and results identified food waste as a promising feedstock. The second traversal compared fermentation coupled with alternative separation techniques, and highlighted that the fed-batch fermentation of food waste integrated with the in-situ separation technique resulted in less environmental impacts. These results will guide experimentalists to further optimize those processes, and improve the environmental sustainability of SL production. Resultant datasets can be iteratively used in subsequent traversals to account for technological changes and mitigate the corresponding impacts before scaling up.