scholarly journals VET workers’ problem-solving skills in technology-rich environments: European approach

2014 ◽  
Vol 1 (1) ◽  
pp. 57-80 ◽  
Author(s):  
Raija Hämäläinen ◽  
Sebastiano Cincinnato ◽  
Antero Malin ◽  
Bram De Wever
Keyword(s):  
Problem Solving ◽  
Large Scale ◽  
Assessment Data ◽  
Problem Solving Skills ◽  
Large Scale Assessment ◽  
Starting Point ◽  
High Level ◽  
Source Of Information ◽  
Insight Into ◽  
Gaining Insight

The European workplace is challenging VET adults’ problem-solving skills in technology-rich environments (TREs). So far, no international large-scale assessment data has been available for VET. The PIAAC data comprise the most comprehensive source of information on adults’ skills to date. The present study (N=50 369) focuses on gaining insight into the problem-solving skills in TREs of adults with a VET background. When examining the similarities and differences in VET adults’ problem-solving skills in TREs across 11 European countries, two main trends can be observed. First, our results show that only a minority of VET adults perform at a high level. Second, there seems to be substantial variation between countries with respect to the proportion of VET adults that can be identified as “at-risk” or “weak” performers. For the future, our findings indicate the variations that can be used as a starting point to identify beneficial VET approaches. 

scholarly journals An error analysis in the early grades mathematics – a learning opportunity?

2014 ◽  
Vol 4 (1) ◽  
pp. 19 ◽  
Author(s):  
Roelien Herholdt ◽  
Ingrid Sapire
Keyword(s):  
Problem Solving ◽  
Error Analysis ◽  
Large Scale ◽  
Mathematical Problem ◽  
Mathematical Problem Solving ◽  
Analysis Method ◽  
Problem Solving Skills ◽  
Scale Error ◽  
And Control ◽  
Insight Into

<p>Error analysis is the study of errors in learners’ work with a view to looking for possible explanations for these errors. It is a multifaceted activity involving analysis of correct, partially correct and incorrect processes and thinking about possible remediating strategies. This paper reports on such an analysis of learner tests. The tests were administered as part of the evaluation of an intervention project that aimed to teach mathematical problem solving skills to grade 1-4 learners. Quantitative error analysis was carried out using a coding sheet for each grade. A reliability coefficient was found for each test, as were item means and discrimination indexes for each item. The analysis provided some insight into the more common procedural and conceptual errors evidenced in the learners’ scripts. Findings showed similar difficulties across intervention and control schools and highlighted particular areas of difficulty. The authors argue that this analysis is an example of large-scale error analysis, but that the analysis method could be adopted by teachers of grades 1-4.</p>

scholarly journals The time on task effect in reading and problem solving is moderated by task difficulty and skill: Insights from a computer-based large-scale assessment.

2014 ◽  
Vol 106 (3) ◽  
pp. 608-626 ◽  
Author(s):  
Frank Goldhammer ◽  
Johannes Naumann ◽  
Annette Stelter ◽  
Krisztina Tóth ◽  
Heiko Rölke ◽  
...  
Keyword(s):  
Problem Solving ◽  
Task Difficulty ◽  
Large Scale ◽  
Time On Task ◽  
Large Scale Assessment ◽  
Scale Assessment ◽  
Task Effect ◽  
Computer Based

Computer Agent Technologies in Collaborative Assessments

2016 ◽  
pp. 319-343 ◽  
Author(s):  
Yigal Rosen ◽  
Maryam Mosharraf
Keyword(s):  
Problem Solving ◽  
Large Scale ◽  
Collaborative Problem Solving ◽  
Future Research ◽  
Educational Systems ◽  
Virtual Agents ◽  
Daily Lives ◽  
Large Scale Assessment ◽  
Collaborative Problem ◽  
Scalable Learning

Often in our daily lives we learn and work in groups. In recognition of the importance of collaborative and problem solving skills, educators are realizing the need for effective and scalable learning and assessment solutions to promote the skillset in educational systems. In the settings of a comprehensive collaborative problem solving assessment, each student should be matched with various types of group members and must apply the skills in varied contexts and tasks. One solution to these assessment demands is to use computer-based (virtual) agents to serve as the collaborators in the interactions with students. The chapter presents the premises and challenges in the use of computer agents in the assessment of collaborative problem solving. Directions for future research are discussed in terms of their implications to large-scale assessment programs.

scholarly journals A Practical Guide for Analyzing Large-Scale Assessment Data Using Mplus: A Case Demonstration Using the Program for International Assessment of Adult Competencies Data

2020 ◽  
pp. 107699862097855
Author(s):  
Takashi Yamashita ◽  
Thomas J. Smith ◽  
Phyllis A. Cummins
Keyword(s):  
Structural Equation ◽  
Large Scale ◽  
Structural Equation Models ◽  
Preparation Process ◽  
Data Preparation ◽  
Assessment Data ◽  
Statistical Software ◽  
Large Scale Assessment ◽  
Scale Assessment ◽  
International Assessment

In order to promote the use of increasingly available large-scale assessment data in education and expand the scope of analytic capabilities among applied researchers, this study provides step-by-step guidance, and practical examples of syntax and data analysis using Mplus. Concise overview and key unique aspects of large-scale assessment data from the 2012/2014 Program for International Assessment of Adult Competencies (PIAAC) are described. Using commonly-used statistical software including SAS and R, a simple macro program and syntax are developed to streamline the data preparation process. Then, two examples of structural equation models are demonstrated using Mplus. The suggested data preparation and analytic approaches can be immediately applicable to existing large-scale assessment data.

scholarly journals Understanding adults’ strong problem-solving skills based on PIAAC

2017 ◽  
Vol 29 (7/8) ◽  
pp. 537-553 ◽  
Author(s):  
Raija Hämäläinen ◽  
Bram De Wever ◽  
Kari Nissinen ◽  
Sebastiano Cincinnato
Keyword(s):  
Problem Solving ◽  
Everyday Life ◽  
Continuous Process ◽  
Vocational Education And Training ◽  
Problem Solving Skills ◽  
Content Type ◽  
Work Related ◽  
Problem Solvers ◽  
Insight Into ◽  
Good Problem

Purpose Research has shown that the problem-solving skills of adults with a vocational education and training (VET) background in technology-rich environments (TREs) are often inadequate. However, some adults with a VET background do have sound problem-solving skills. The present study aims to provide insight into the socio-demographic, work-related and everyday life factors that are associated with a strong problem-solving performance. Design/methodology/approach The study builds on large-scale data of the Programme for the International Assessment of Adult Competencies (PIAAC) and gives insight into VET adults (N = 12,929) with strong problem-solving skills in 11 European countries. Findings This study introduces new knowledge with respect to the socio-demographic, work-related and everyday life background factors that contribute to successful VET adults’ problem-solving skills. The findings of the authors illustrate that a continuous process of development including non-formal and informal activity, as well as learning taking place at work, is associated with strong performance in problem-solving skills in TRE. Research limitations/implications An important implication of this study is that this paper introduces novel knowledge for VET adults’ competences and can be used to support the development of VET adults’ problem-solving skills in TREs. Originality/value The study was conducted to explore new understanding about good problem-solvers in TREs with a VET background. The originality of the study derives from its focus on good problem-solvers in TREs related to a VET background. The findings can be used to create novel ways to enhance the development of VET adults’ problem-solving skills in TREs.

Basic numerical competences in large-scale assessment data: Structure and long-term relevance

2018 ◽  
Vol 167 ◽  
pp. 32-48 ◽  
Author(s):  
Stefa Hirsch ◽  
Katharina Lambert ◽  
Karien Coppens ◽  
Korbinian Moeller
Keyword(s):  
Data Structure ◽  
Large Scale ◽  
Assessment Data ◽  
Large Scale Assessment ◽  
Scale Assessment
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