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Dynamic Testing of Learning Potential of Children with Moderate to Severe Intellectual Disabilities: A Delphi Study

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Title: Dynamic Testing of Learning Potential of Children with Moderate to Severe Intellectual Disabilities: A Delphi Study
Language: English
Authors: M. L. Eding (ORCID 0000-0002-9357-2184), M. Meeter, C. Schuengel
Source: Journal of Research in Special Educational Needs. 2025 25(1):32-43.
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 12
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Descriptors: Delphi Technique, Moderate Intellectual Disability, Severe Intellectual Disability, Foreign Countries, Child Care Centers, Special Schools, Check Lists, Task Analysis, Psychological Testing, Testing, Specialists, Educational Assessment, Preschool Children, Logical Thinking
Geographic Terms: Netherlands
DOI: 10.1111/1471-3802.12706
ISSN: 1471-3802
Abstract: Education of children with moderate to severe intellectual disabilities requires adequate assessment of their educational needs and potential to learn. Dynamic testing using analogical reasoning tasks may be a promising way to perform such an assessment. However, it remains unclear how dynamic testing with these children may be done in practice. Therefore, we sought expert opinions on operationalizing learning potential and dynamic testing. We performed a three-round online Delphi study (N = 37) with experts in psychological educational assessment of children with moderate to severe intellectual disabilities in special schools and specialized day-care centres in the Netherlands. Consensus was found on a conceptual and an operational definition of learning potential, describing step-by-step how learning potential could be measured in daily practice. This included a pre-test, training, post-test design with the inclusion of a graduated prompts protocol for mediation and an observation checklist focussing on response to mediation. Based on examples from the Analogical Reasoning Learning Test, we assessed consensus on adapted design requirements for dynamic testing using analogical reasoning. Experts agreed that dynamic testing using analogical reasoning tasks might be suitable for children with moderate intellectual disabilities. A key concern was whether performance on analogical reasoning task was within reach of children with severe intellectual disabilities. The panel recommended research into the type of mediation needed to support the learning of analogical reasoning tasks. Further development and evaluation of dynamic testing for children with moderate to severe intellectual disabilities may build on the recommendations of this panel of experts.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1456695
Database: ERIC
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  Value: <anid>AN0183979959;0lc01jan.25;2025Mar26.05:31;v2.2.500</anid> <title id="AN0183979959-1">Dynamic testing of learning potential of children with moderate to severe intellectual disabilities: A Delphi study </title> <p>Education of children with moderate to severe intellectual disabilities requires adequate assessment of their educational needs and potential to learn. Dynamic testing using analogical reasoning tasks may be a promising way to perform such an assessment. However, it remains unclear how dynamic testing with these children may be done in practice. Therefore, we sought expert opinions on operationalizing learning potential and dynamic testing. We performed a three‐round online Delphi study (N = 37) with experts in psychological educational assessment of children with moderate to severe intellectual disabilities in special schools and specialized day‐care centres in the Netherlands. Consensus was found on a conceptual and an operational definition of learning potential, describing step‐by‐step how learning potential could be measured in daily practice. This included a pre‐test, training, post‐test design with the inclusion of a graduated prompts protocol for mediation and an observation checklist focussing on response to mediation. Based on examples from the Analogical Reasoning Learning Test, we assessed consensus on adapted design requirements for dynamic testing using analogical reasoning. Experts agreed that dynamic testing using analogical reasoning tasks might be suitable for children with moderate intellectual disabilities. A key concern was whether performance on analogical reasoning task was within reach of children with severe intellectual disabilities. The panel recommended research into the type of mediation needed to support the learning of analogical reasoning tasks. Further development and evaluation of dynamic testing for children with moderate to severe intellectual disabilities may build on the recommendations of this panel of experts.</p> <p>Keywords: Delphi study; dynamic testing; learning potential; moderate to severe intellectual disabilities</p> <hd id="AN0183979959-2">Key Points</hd> <p></p> <ulist> <item> All children have the potential to learn. Dynamic testing has been proposed for testing learning potential and assessing the type of support a child needs to realize this potential.</item> <p></p> <item> Experts found consensus on a conceptual and an operational definition of learning potential, that may guide the development of dynamic tests for children with moderate and severe intellectual disabilities.</item> <p></p> <item> Analogical reasoning tasks were deemed appropriate by the experts to measure learning potential for children with moderate intellectual disabilities. Adaptations were suggested in materials used, content and build‐up of difficulty levels, and length of the training phase.</item> <p></p> <item> For children with severe intellectual disabilities further research was advised as experts stated these children may not yet possess the skills needed to solve analogical reasoning tasks and may need more or other forms of training.</item> </ulist> <hd id="AN0183979959-3">INTRODUCTION</hd> <p>The Salamanca Statement (UNESCO, [<reflink idref="bib48" id="ref1">48</reflink>]), which was signed by 92 governments and 25 international organizations, states that every child has a fundamental right to education and must be given the opportunity to achieve and maintain an acceptable level of learning. Children with moderate to severe intellectual disabilities, even more so than other children, need personalized educational support to learn and benefit from education (Bosson et al., [<reflink idref="bib8" id="ref2">8</reflink>]; Buchel, [<reflink idref="bib10" id="ref3">10</reflink>]; Caffrey & Fuchs, [<reflink idref="bib12" id="ref4">12</reflink>]). Such educational support may require assessment of what and how children can learn (Bosma & Resing, [<reflink idref="bib6" id="ref5">6</reflink>]), following the concept of the zone of proximal development (Vygotsky & Cole, [<reflink idref="bib53" id="ref6">53</reflink>]). Assessment of learning needs is complicated by the functional needs that go along with moderate and severe intellectual disabilities. According to the DSM‐5‐TR (APA, [<reflink idref="bib1" id="ref7">1</reflink>]), moderate and severe intellectual developmental disorders (intellectual disabilities) involve significant impairments of intellectual and adaptive functioning that require intensive support for conceptual, social and practical functioning. Addressing these functional needs requires assessment while at the same time making such assessment difficult.</p> <p>Intelligence tests alone are not sufficient for the assessment of educational needs because they may underestimate the true capacities of 'at risk' children (Bosma & Resing, [<reflink idref="bib6" id="ref8">6</reflink>]; Hessels‐Schlatter, [<reflink idref="bib26" id="ref9">26</reflink>]; Tiekstra et al., [<reflink idref="bib44" id="ref10">44</reflink>]). Intelligence tests are also neither intended nor standardized for children with moderate to severe intellectual disability, as their scores often show floor effects which makes the outcomes less reliable, discriminating, and informative. Non‐intellectual factors that influence learning, such as intrinsic motivation, frustration tolerance and perseverance, are not assessed (Tzuriel, [<reflink idref="bib45" id="ref11">45</reflink>]). Interpretation of intelligence test scores is also complicated by differences in the opportunities that children have to acquire the skills and abilities being assessed (Elliott, [<reflink idref="bib17" id="ref12">17</reflink>]; Grigorenko, [<reflink idref="bib23" id="ref13">23</reflink>]). Children with moderate to severe intellectual disabilities may have lacked the tailored learning experiences that they needed for developing their cognitive functioning (Hessels‐Schlatter, [<reflink idref="bib26" id="ref14">26</reflink>]) and may require assessments that take into account the level of support they received and other environmental factors that affect their cognitive functioning (Carlson & Wiedl, [<reflink idref="bib14" id="ref15">14</reflink>]; Grigorenko, [<reflink idref="bib23" id="ref16">23</reflink>]). Therefore, the conclusion that poor performance on a standardized intelligence test is indicative of poor ability to learn may not be justified, especially for children with intellectual disabilities (Beckmann, [<reflink idref="bib3" id="ref17">3</reflink>]).</p> <p>Dynamic assessment may be a more suitable way to assess the ability to learn, as it provides information on how children benefit from training (Grigorenko, [<reflink idref="bib23" id="ref18">23</reflink>]; Tiekstra et al., [<reflink idref="bib44" id="ref19">44</reflink>]) and links educational needs with individual learning variability (Bosma & Resing, [<reflink idref="bib7" id="ref20">7</reflink>]). The description of educational needs can be seen as an important step to guide tailored educational interventions (Bosma & Resing, [<reflink idref="bib7" id="ref21">7</reflink>]). Common in all forms of dynamic assessment is the incorporation of training in the assessment procedure. The effects of this training on performance indicate a child's learning potential (Boosman et al., [<reflink idref="bib5" id="ref22">5</reflink>]; Elliott et al., [<reflink idref="bib18" id="ref23">18</reflink>]). Different views on dynamic assessment exist and multiple assessment procedures have been developed (Green & Birch, [<reflink idref="bib22" id="ref24">22</reflink>]). An often‐mentioned distinction is between dynamic assessment on the one hand and dynamic testing on the other hand. Dynamic assessment focusses on individualized and non‐standardized mediation of cognitive change (e.g. Feuerstein et al., [<reflink idref="bib20" id="ref25">20</reflink>]; Tzuriel, [<reflink idref="bib45" id="ref26">45</reflink>]). Dynamic testing, which is the focus of our current study, assesses learning potential by using an objective, standardized, and repeatable testing procedure (Resing, Elliot, & Grigorenko, [<reflink idref="bib36" id="ref27">36</reflink>]). A dynamic test usually includes a pre‐test, training, post‐test design (Caffrey et al., [<reflink idref="bib13" id="ref28">13</reflink>]). The progress in learning from pre‐ to post‐test and the instructions needed in the training phase to reach this progress are seen as important indicators of learning potential (Sternberg & Grigorenko, [<reflink idref="bib41" id="ref29">41</reflink>]; Haywood and Lidz, [<reflink idref="bib25" id="ref30">25</reflink>]). Children with intellectual disabilities with comparable IQ‐sores varied in their progress during dynamic testing, suggesting variation in learning potential (Bosma & Resing, [<reflink idref="bib7" id="ref31">7</reflink>]; Lifshitz et al., [<reflink idref="bib30" id="ref32">30</reflink>]).</p> <p>Research on dynamic testing for children with moderate to severe intellectual disabilities is still limited (e.g. Bosma & Resing, [<reflink idref="bib7" id="ref33">7</reflink>]; Buchel, [<reflink idref="bib10" id="ref34">10</reflink>]; Budoff, [<reflink idref="bib11" id="ref35">11</reflink>]; Hessels‐Schlatter, [<reflink idref="bib26" id="ref36">26</reflink>]; Saldana, [<reflink idref="bib38" id="ref37">38</reflink>]; Tzuriel & Klein, [<reflink idref="bib47" id="ref38">47</reflink>]). Bosma and Resing, who used a dynamic test for children with mild to moderate intellectual disabilities, found that dynamically tested children achieved significantly higher post test scores than untrained children. Budoff demonstrated that in participants with IQs below 50, a dynamic measure (Kohs Learning Potential Task) outperformed static measures in predicting achievement, and several students with low IQ scores reached a higher level of functioning and reasoning after a short training. The work of Tzuriel and Klein focused on students with moderate intellectual disabilities and showed that a dynamic test differentiated between students' levels of performance to infer and apply rules after training. Saldana stated that collaborative interaction in a dynamic version of the game Mastermind might tap into underlying capabilities of persons with severe cognitive difficulties.</p> <p>Dynamic tests often use analogical reasoning tasks, which are considered crucial for cognitive development and for learning in school (Vogelaar et al., [<reflink idref="bib51" id="ref39">51</reflink>]). Analogical reasoning concerns the ability to perceive and use relational difference and similarity between two situations or concepts to make inferences or solve problems. Dynamic tests using analogical reasoning have been argued to provide a better estimate of future learning than a static intelligence test (Caffrey et al., [<reflink idref="bib13" id="ref40">13</reflink>]; Lifshitz et al., [<reflink idref="bib30" id="ref41">30</reflink>]; Sternberg & Grigorenko, [<reflink idref="bib41" id="ref42">41</reflink>]). Children with intellectual disabilities show lower initial performance in analogical reasoning than typically developing children but may acquire analogical reasoning through training (Bosson et al., [<reflink idref="bib8" id="ref43">8</reflink>]; Lifshitz et al., [<reflink idref="bib31" id="ref44">31</reflink>]; Schlatter & Büchel, [<reflink idref="bib39" id="ref45">39</reflink>]).</p> <p>The Analogical Reasoning Learning Test (ARLT) provides a concrete example of a dynamic test of learning potential for children with IQ scores below 50–55 on a static intelligence test (Hessels‐Schlatter, [<reflink idref="bib26" id="ref46">26</reflink>]). The ARLT consists of analogical matrixes of varying difficulty levels (see Figure 1 for example). Children are first taught prerequisite concepts for taking the test (e.g. inferring the concepts of same and different). Subsequently two training sessions are given, followed by a post‐test which measures the independent performance of the child after training. The ARLT proved to be a reliable and valid instrument to assess learning potential and differentiate children who would benefit from a more extensive cognitive training from those for whom this would be too demanding. The ARLT provided a base model in our study for the design of a prototype of a dynamic test for children with moderate to severe intellectual disabilities.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/0LC/01jan25/jrs312706-fig-0001.jpg?ephost1=dGJyMNHX8kSepq84v%2bvlOLCmsE6epq5Srqa4SK6WxWXS" alt="jrs312706-fig-0001.jpg" title="1 An example of an analogical matrix in the ARLT." /> </p> <p></p> <p>Dynamic tests seem at the moment to be scarcely used with children with moderate to severe intellectual disabilities who attend special schools or specialized day‐care centres in the Netherlands. The wider proliferation of dynamic testing of these children may be held back by a lack of clarity and operationalisation of the key concepts used and the envisioned purposes of use, which are described as essential in the development of dynamic tests (Caffrey et al., [<reflink idref="bib13" id="ref47">13</reflink>]; Elliott et al., [<reflink idref="bib19" id="ref48">19</reflink>]). Definitions employed for children in regular education (Resing, [<reflink idref="bib33" id="ref49">33</reflink>]), children with language impairments (Peña et al., [<reflink idref="bib32" id="ref50">32</reflink>]) and gifted children (Vogelaar et al., [<reflink idref="bib52" id="ref51">52</reflink>]) may provide a useful starting point for developing definitions that are suitable for children with moderate to severe intellectual disabilities. Also, conceptual work about adapting dynamic tests to make them suitable for children with moderate to severe intellectual disabilities is needed, because the variety in levels of understanding, learning experiences and need for instruction combined with comorbid problems such as visual, hearing and motor limitations make the development of dynamic tests for this group challenging (Boers, [<reflink idref="bib4" id="ref52">4</reflink>]).</p> <p>Therefore, following Beck ([<reflink idref="bib2" id="ref53">2</reflink>]), in a 3‐round Delphi Study we collected and synthesized expert knowledge and opinions on defining and operationalizing learning potential and dynamic testing, answering the following research questions.</p> <p></p> <ulist> <item> What are current and potential practices around the concepts of learning potential and dynamic testing of children with moderate to severe intellectual disabilities?</item> <p></p> <item> How should learning potential of children with moderate to severe intellectual disabilities be conceptually and operationally defined?</item> <p></p> <item> How should a dynamic test for analogical reasoning be designed for children with moderate to severe intellectual disabilities?</item> </ulist> <hd id="AN0183979959-5">METHOD AND MATERIALS</hd> <p></p> <hd id="AN0183979959-6">Design</hd> <p>We used an online Delphi study of three rounds, which had the advantage of time‐effectiveness and enabled experts from various locations to participate. Participants were anonymous, so opinions could be expressed freely. Participants were informed in advance about the goals, content, and time required for the Delphi study. Informed consent forms were filled in by all participants. Participants could exit and withdraw from the study at any time. In describing the methods and results of the Delphi study, this paper follows the guidelines of Spranger et al. ([<reflink idref="bib40" id="ref54">40</reflink>]).</p> <hd id="AN0183979959-7">Sample</hd> <p>We used purposive sampling and partial snowballing methods to select a panel of participants who had at least 1 year of expertise in psychological educational assessment of children with moderate to severe intellectual disabilities, as shown in Table 1. Informed consent forms were filled in by 40 participants who met the inclusion criteria and 37 filled in the first questionnaire. Of the latter group, 12 worked in special schools, 18 in specialized day‐care where children also received education (in different forms) and 17 worked at a setting providing combined education and care or outpatient clinics. Criteria for inclusion were kept broad so that opinions would reflect the current state of the art in the field (Hasson et al., [<reflink idref="bib24" id="ref55">24</reflink>]).</p> <p>1 TABLE Overview of sample.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th align="left">Number</th><th align="left">%</th></tr></thead><tbody valign="top"><tr><td align="left">Function</td></tr><tr><td align="left">Orthopedagogue<xref ref-type="fn" rid="tfn1" /></td><td align="left">20</td><td align="left">54</td></tr><tr><td align="left">Psychologist</td><td align="left">7</td><td align="left">19</td></tr><tr><td align="left">Psychodiagnostics worker</td><td align="left">5</td><td align="left">13</td></tr><tr><td align="left">In school support worker</td><td align="left">1</td><td align="left">3</td></tr><tr><td align="left">Other (combination of functions, teacher with diagnostic tasks)</td><td align="left">4</td><td align="left">11</td></tr><tr><td align="left" /><td align="left">37</td><td align="left">100</td></tr><tr><td align="left">Years of diagnostic experience</td></tr><tr><td align="left">0</td><td align="left">0</td><td align="left">0</td></tr><tr><td align="left">1–4</td><td align="left">12</td><td align="left">32</td></tr><tr><td align="left">5–10</td><td align="left">8</td><td align="left">22</td></tr><tr><td align="left">>10</td><td align="left">17</td><td align="left">46</td></tr><tr><td align="left" /><td align="left">37</td><td align="left">100</td></tr><tr><td align="left">Current employment location</td></tr><tr><td align="left">Special schools</td><td align="left">12</td><td align="left">26</td></tr><tr><td align="left">Day‐care centre</td><td align="left">18</td><td align="left">39</td></tr><tr><td align="left">Other (combination care/education, outpatient clinic, multiple locations)</td><td align="left">16</td><td align="left">35</td></tr><tr><td align="left" /><td align="left">37</td><td align="left">100</td></tr></tbody></table> </ephtml> </p> <p>1 a Dutch term for an academic certified consultant in parenting, education, and development.</p> <hd id="AN0183979959-8">Data collection</hd> <p>Data was collected between July and December 2022 in three successive rounds through an online questionnaire (Qualtrics, version 2019). Questionnaires were sent by e‐mail; 2 weeks later a reminder e‐mail was sent. Participants were invited to participate in each round, regardless of their participation in previous rounds. Response rates in the successive rounds, shown in Figure 2, were high.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/0LC/01jan25/jrs312706-fig-0002.jpg?ephost1=dGJyMNHX8kSepq84v%2bvlOLCmsE6epq5Srqa4SK6WxWXS" alt="jrs312706-fig-0002.jpg" title="2 Response rates per round." /> </p> <p></p> <hd id="AN0183979959-10">Procedure and data analysis</hd> <p></p> <hd id="AN0183979959-11">Preparation phase</hd> <p>We reviewed the literature and consulted leading experts in the field of dynamic assessment. This led to using the Analogical Reasoning Learning Test as a base model in our study for the design of a prototype of a dynamic test for children with moderate to severe intellectual disabilities. The prototype guided the development of the questionnaires in the Delphi study.</p> <p>First, we translated the ARLT into Dutch and added a pre‐test—training—post‐test design. To establish the rate in which children benefit from a training phase, regardless of their starting level, the use of a pre‐test as a base‐line measure is advised (Veerbeek et al., [<reflink idref="bib49" id="ref56">49</reflink>]) to calculate gain scores. Gain scores, defined as the difference in scores between pre‐ and post‐test, are considered an objective quantitative measure of learning potential (Resing, Elliot, & Grigorenko, [<reflink idref="bib36" id="ref57">36</reflink>]; Resing & Elliott, [<reflink idref="bib37" id="ref58">37</reflink>]). We also added a protocol of graduated prompts in the training to assess in a standardized way the amount and type of instruction a child needs to solve a task (Elliott et al., [<reflink idref="bib18" id="ref59">18</reflink>]; Resing et al., [<reflink idref="bib35" id="ref60">35</reflink>]). If a child answers incorrectly, the level of prompting becomes gradually more explicit until a child reaches the correct answer. We used the graduated prompts protocol as suggested by Visser et al. ([<reflink idref="bib50" id="ref61">50</reflink>]) in their work on the dynamic version of the Bayley‐III‐NL, as we expected this to be the best fit for our target population. Prompting starts with repeating the instruction, proceeding to verbally explaining, then demonstrating and finally finishing the task hand‐over‐hand together with the child. The number of prompts together with gain scores, are considered an indicator of learning potential. Finally, we added an observation checklist, focusing on the child's response to the training. For this purpose, we translated the Response to Mediation Scale, originally developed by Lidz ([<reflink idref="bib29" id="ref62">29</reflink>]) for the dynamic assessment of young children.</p> <hd id="AN0183979959-12">Round 1</hd> <p>Open‐ended questions were included to gain as much information as possible about the current and potential use of the concept of learning potential and dynamic testing in psychological educational assessment in special schools or specialized‐day care centres in the Netherlands. Open‐ended questions were used because limited knowledge on this topic was available. The first author conducted a thematic content analysis of the descriptions and indicators of learning potential. The research group discussed and adjusted the analysis until consensus was reached (Graneheim & Lundman, [<reflink idref="bib21" id="ref63">21</reflink>]). Based on this analysis a provisional conceptual definition and an operational definition of learning potential were formulated by the research team and submitted in Round 2.</p> <p>Also, rating scale questions about the perceived value of learning potential and dynamic testing in relation to static intelligence testing were included. We used Likert scales to determine consensus on rating scale questions. In our study, following Boulkedid et al. ([<reflink idref="bib9" id="ref64">9</reflink>]), consensus was a priori defined as ≥70% agreement in answers.</p> <hd id="AN0183979959-13">Round 2</hd> <p>Participants received summarized results of round 1, including the provisional conceptual and operational definition of learning potential. Using 4‐point Likert scales, consensus on completeness, comprehensibility, and relevance of the provisional definitions was assessed. We also assessed usability of six categories of test design requirements, based on the ARLT. If consensus was not found, items were adapted and submitted in Round 3. For every rating‐scale question, participants were invited to clarify their answers. This information was qualitatively analysed and used to revise the definitions and test design requirements.</p> <hd id="AN0183979959-14">Round 3</hd> <p>This final round assessed consensus on the revised definitions and test design requirements.</p> <hd id="AN0183979959-15">RESULTS</hd> <p>In this paragraph the results are presented per research question. Quantitative results from rating scale questions and qualitative data from open‐ended questions or comments are described together.</p> <hd id="AN0183979959-16">Research question 1: What are current and potential practices around the concepts of learning...</hd> <p>Most (76%) participants endorsed the relevance of the concept of learning potential and used it in their work. They used mainly information derived from observations, interviews with teachers, and different testing‐to‐the‐limit procedures to describe the learning potential of a child.</p> <p>'I follow the standard testing procedure and adjust this if a child is not responding sufficiently. I repeat instruction, practice more intensively, offer instruction differently (...) to examine what a child to needs understand the assignment.' <Respondent (R) 23></p> <p>No dynamic tests of learning potential were used because participants lacked a clear definition and a valid and reliable dynamic test for these children. However, all participants stated that they would use a dynamic test if this was available. Frequently mentioned purposes of use were formulating learning goals and educational needs and clarifying stagnations in the learning process.</p> <p>A consensus was found on the value of learning potential, alone or in combination with static IQ scores. Participants agreed that learning potential scores better estimated the learning possibilities of a child (77%) and provided more useful information for education (78%) than a static IQ test alone. Reasons given were that dynamic tests include both cognitive and non‐cognitive variables influencing learning and follow the learning process during a longer period, thereby providing a broader picture, especially for children with intellectual disabilities.</p> <p>'It is not important to know a child scores low on an IQ test, but to know what he/she needs to be able to complete a learning task and develop further.' <R4></p> <p>Consensus was not found on whether a dynamic test should be used instead of or in combination with a static intelligence test. Many participants (56%) would use both as this would provide a more comprehensive view of the strengths and needs of a child and fulfil the requirement in the Dutch care system for IQ‐scores when applying for special needs support. Yet, a minority of 21% of the participants would only use a dynamic test, because they evaluated static intelligence tests as unreliable for children with moderate to severe intellectual disabilities.</p> <hd id="AN0183979959-17">Research question 2: How should learning potential of children with moderate to severe intell...</hd> <p>In Round 3, consensus was reached on both a conceptual and operational definition of learning potential. In Round 1, participants were asked how they would define learning potential. Learning potential was described as a combination of cognitive (e.g. learning progress, zone of proximal development, transfer of learned skills, instructional needs) and affective (e.g. perseverance, internal motivation, openness to instruction) characteristics of a child. Also, context variables influencing the actual development of learning potential were considered important, especially the type of instructions, the expectations of the teacher and the organization of the learning context (e.g. student to teacher ratio, size of class).</p> <p>As uniformity in underlying concepts is a prerequisite for further development of valid and reliable dynamic tests, the research team developed a provisional conceptual and operational definition of learning potential. For this, descriptions from round 1 were complemented with definitions derived from previous research (e.g. Resing, [<reflink idref="bib34" id="ref65">34</reflink>]; Tzuriel, [<reflink idref="bib46" id="ref66">46</reflink>]). The provisional definitions were inserted in Round 2 of the Delphi study. Based on the results of Round 2 these definitions were adapted and subsequently consensus was reached in Round 3, which can be found in Table 2.</p> <p>2 TABLE Overview of conceptual and operational definitions developed in Rounds 2 and 3, with in bold the changes made after Round 2 to reach consensus.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Provisional definition Round 2</th><th align="left">Consensus definition Round 3</th></tr></thead><tbody valign="top"><tr><td align="left">Conceptual definition</td></tr><tr><td align="left">Learning potential is the extent to which a child can learn and apply new knowledge and skills, with adequate help and instruction and within a given time</td><td align="left">Learning potential is what a child can learn and apply in terms of new knowledge and skills, with appropriate help, instruction, and time</td></tr><tr><td align="left">Operational definition</td></tr><tr><td align="left">Learning potential is measured by the progress in learning performance from pre‐ to post‐test after a predetermined and standardized training phase and the amount and type of instruction needed to achieve this progressLearning potential is measured in several steps:<list list-type="Bullet"><list-item><p>Assess unaided performance of a child on a certain task (pre‐test: current level of knowledge and development)</p></list-item><list-item><p>Train a child to perform a certain task in a structured way within a predetermined period</p></list-item><list-item><p>Assess what a child has learned during the training (post‐test: assess the difference in performance from pre‐ to post‐test)</p></list-item><list-item><p>Assess how a child learned this (observe response to instruction and assess type and amount of instruction a child needed)</p></list-item></list></td><td align="left">Learning potential is measured by the progress in learning performance from pre‐ to post‐test after a predetermined and semi‐standardized training phase and the amount and type of instruction needed to achieve this progressLearning potential is measured in several steps:<list list-type="Bullet"><list-item><p>Assess unaided performance of a child on a certain task (pre‐test: current level of knowledge and development on this task)</p></list-item><list-item><p>Train a child to perform a certain task in a semi‐structured way within a predetermined period</p></list-item><list-item><p>Assess what a child has learned during the training (post‐test: assess the difference in performance from pre‐ to post‐test)</p></list-item><list-item><p>Assess how a child learned this (observe response to instruction and assess type and amount of instruction a child needed)</p></list-item><list-item><p>Assess if the child applied what he/she learned to other similar and more complex tasks (transfer)</p></list-item></list></td></tr></tbody></table> </ephtml> </p> <hd id="AN0183979959-18">Conceptual definition</hd> <p>In Round 2, consensus was found on comprehensibility (83%) and usability (75%) of the provisional conceptual definition. Participants agreed that the conceptual definition, being short and concrete, was easy to understand and to apply to daily practice. Consensus was not found in Round 2 on completeness (67%), as the inclusion of 'learning within a certain period' raised questions because children with moderate to severe intellectual disabilities would need more time to process instructions and show learning potential.</p> <p>'Does a child not have potential if he does not master certain knowledge or skills within the pre‐set period? Each child develops at a different pace, children with severe intellectual disabilities take a lot of time to learn, but they can learn and do have potential. However, in a dynamic test, you want to see if and how a child progresses after training, so inclusion of time as a factor would be relevant.' <R16></p> <p>The research team adapted the conceptual definition and consensus was reached in Round 3 (70%, Table 2).</p> <hd id="AN0183979959-19">Operational definition</hd> <p>For the operational definition, in Round 2 consensus was reached on comprehensibility (89%) and usability (83%). Participants agreed that the operational definition provided a usable step‐by‐step guide for measuring learning potential. The emphasis on response to training and type and amount of training was seen as valuable for organizing educational support. Consensus was not found on completeness (69%), mostly because several participants deemed it necessary to include the transfer of learned skills to assess if children could apply acquired skills to new and more complex tasks. Also, participants stated that while standardization would be necessary for replicability and objectivity, adaptation of tests to individual needs was essential to reveal potential. Therefore, participants argued that training should be semi‐standardized.</p> <p>'In certain situations, you have to move along with a child and leave the protocol, in order to reveal the true potential of a child.' <R36></p> <p>Subsequently, in Round 3 consensus was reached on the adapted operational definition (91%; Table 2).</p> <hd id="AN0183979959-20">Research question 3: How should a dynamic test for analogical reasoning be designed for child...</hd> <p>Based on concrete examples from the ARLT (Hessels‐Schlatter, [<reflink idref="bib26" id="ref67">26</reflink>]), in Table 3 six categories of design requirements that participants agreed on are described.</p> <p>3 TABLE Overview of design requirements on which consensus was reached, with percentage of agreement.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left">Category</th><th align="left">%</th></tr></thead><tbody valign="top"><tr><td align="left">Structure</td></tr><tr><td align="left">Pre‐test, training, post‐testTransfer task included in post‐testMultiple training moments, with graduated promptsObservation checklist in training</td><td align="left">9497100100</td></tr><tr><td align="left">Outcome measures</td></tr><tr><td align="left">Quantitative:Gain‐scores (difference from pre‐ to post‐test)Amount of instruction neededTransfer scores post‐testQualitative:Type of prompts neededResponse to training (observation checklist)</td><td align="left">949297100100</td></tr><tr><td align="left">Materials</td></tr><tr><td align="left">Picture cards as in ARLT usableAdd tangible materials</td><td align="left">83100 (MID)<xref ref-type="fn" rid="tfn2" />66 (SID)<xref ref-type="fn" rid="tfn2" /></td></tr><tr><td align="left">Build‐up difficulty levels</td></tr><tr><td align="left">Add sorting/matching and comparing tasks preceding perceptual analogy tasksAdd tasks using tangible materials</td><td align="left">100 (MID)<xref ref-type="fn" rid="tfn2" />66 (SID)<xref ref-type="fn" rid="tfn2" />88 (MID)<xref ref-type="fn" rid="tfn2" />32 (SID)<xref ref-type="fn" rid="tfn2" /></td></tr><tr><td align="left">Administering of test</td></tr><tr><td align="left">Non‐verbalStopping rules (3–5 attempts) pre‐ /post‐testVerbalizing answers is not part of test</td><td align="left">947170</td></tr></tbody></table> </ephtml> </p> <p>2 a MID, mild intellectual disability; SID, severe intellectual disability.</p> <hd id="AN0183979959-21">Structure</hd> <p>Consensus was reached in Round 2 on a structure of a dynamic test that aligned with the operational definition of learning potential as described in paragraph 3.2. This structure differs from the example of the ARLT as it includes a pre‐test as a baseline for calculating gain scores, a protocol of graduated prompts, and an observation checklist to systematically observe response to training, which were not present in the ARLT.</p> <hd id="AN0183979959-22">Outcome measures</hd> <p>In Round 2, consensus was reached on both quantitative and qualitative outcome‐measures, as summarized in Table 3. Participants commented that quantitative outcome measures were important to indicate the amount, speed, and internalization of learning and the intensity and amount of educational support needed. Qualitative outcome measures were assumed to provide useable information for organizing educational support, which participants considered the most relevant contribution of dynamic testing.</p> <p>'For me, the value of dynamic testing is examining what a child needs to learn and not to classify a child as having high or low learning potential. If we adapt the learning environment all children will show potential.' <R22></p> <p>For the observation checklist, we translated the Response to Mediation Scale (Lidz, [<reflink idref="bib29" id="ref68">29</reflink>]), which includes cognitive (e.g. attention, comprehension of task, asking for help, responsiveness to help, strategy use) and emotional (e.g. motivation, interaction with examiner, perseverance, interest in materials) behaviours. Consensus was reached in Round 3 on all items. In their comments several participants added the importance of including the role and skills of the examiner in the observation checklist.</p> <hd id="AN0183979959-23">Materials</hd> <p>In Round 2, consensus was found on the usability of picture cards put in a wooden frame, as in the ARLT, to present perceptual analogies. However, experts advised tangible materials as a learning step towards picture cards, as picture cards might be too difficult at once, especially for children with severe intellectual disabilities.</p> <p>'I wonder if children with severe to moderate intellectual disabilities are capable of reasoning with pictures or require tangible objects in this regard.' <R21></p> <p>Participants suggested using tangible materials recognizable from daily life, such as balls, cars, fruits, or toy‐animals, and to avoid distracting details. Participants found it essential to adapt materials to visual and motor limitations often present in children with moderate to severe intellectual disabilities, by use of colour, size, or contrast.</p> <p>'The more tangible, concrete, manipulable and colourful the materials, the more we expect them to match the needs and developmental level of these children.' <R34></p> <p>Furthermore, participants stated that tangible materials offered good possibilities for observing task performance and strategy use.</p> <hd id="AN0183979959-24">The build‐up in difficulty levels</hd> <p>Consensus was not found in Round 2 on the achievability of perceptual analogies as used in the ARLT (67%) and the build‐up in difficulty levels from simplified to multiple perceptual analogies (52%). Participants stated that especially children with severe intellectual disabilities might not yet possess the skills needed to solve perceptual analogies.</p> <p>'I think basic skills in communication, understanding of pictures and knowledge about differences in size, number, colour, and shape are needed for this task. I wonder if children possess these.' <R22></p> <p>Matching, sorting, and comparing are seen as learning steps preceding solving of perceptual analogy tasks (Denaes, [<reflink idref="bib15" id="ref69">15</reflink>]). In Round 3 participants consented that including matching, sorting, and comparing would make a dynamic test using analogical reasoning suitable for children with moderate intellectual disabilities. For children with severe intellectual disabilities consensus was not found and 34% of the participants questioned if these children would even learn within a predetermined training period to match, sort, and compare. However, many participants stated that this adjustment increased the chances of reaching a learning effect and advised to evaluate this in practice.</p> <hd id="AN0183979959-25">Training phase</hd> <p>In Round 2, consensus was found that standardized training was needed for an objective comparison of results. The 2 × 30 min training, as proposed in the ARLT, was considered too short to reveal potential, due to a low learning rate.</p> <p>'If a child does not show progress in learning within the pre‐stated time, this does not mean he/she does not have learning potential, it simple shows he/she was not able to show his potential within this pre‐set time. You cannot tell what he/she might be able to do when given more time and help.' <R16></p> <p>When given four options, consensus was not reached on the best suitable training period. Answers varied from 3 × 30 min (34%), training until a prescribed criterium for example a child can solve two tasks on a row without help (41%), to multiple or daily training by the teacher or examiner (21%). Several participants emphasized finding a balance between training tailored to the concentration, motivation, and previous learning experiences of a child on the one hand and the practical usability of the dynamic test on the other hand.</p> <p>'As appealing as it sounds to lengthen a training phase to provide a child maximal learning opportunity, organising four training sessions into my work is already challenging. Besides, what you want is to assess learning potential and not to give a child a success experience.' <R32></p> <hd id="AN0183979959-26">Test administration</hd> <p>Consensus was found in Round 2 that instructions and materials should enable non‐verbal testing (94%). Participants commented that children with moderate to severe intellectual disabilities sometimes do not talk and that their verbal understanding may exceed their active use of language. In Round 3 consensus was found that children's verbalisation of answers, as described in the ARLT, should not be mandatory because encouraging verbalisation may lead to frustration due to limited verbal capacities, which leaves unclear what is measured: learning potential, communication skills, or frustration. However, verbalisation could be encouraged if children have sufficient capacities to verbalize, as this might enhance their learning.</p> <p>'Verbalizing is crucial for assessing which learning strategy a child uses so you can mediate on that, that is why it is so difficult to develop a dynamic test for non‐speaking children.' <R22></p> <p>'It would be most unfortunate if nonspeaking children would not be included, they also have a potential to learn, and you would want to assess this to provide these children adequate support to realize their potential.' <R19></p> <p>To prevent failure experiences and frustration, in round 3 participants endorsed the suggestion to include stopping rules in the pre‐ and post‐test. In the comments, participants stated that a child had to get a fair chance to understand the instruction and learn from repeated mistakes, therefore enough attempts (3–5) would be necessary.</p> <p>'Sometimes a child will successfully complete a task after failing on preceding tasks, therefore multiple attempts must be given, the Bayley‐III for example uses five attempts and then you can observe more learning behaviour and progress.' <R31></p> <hd id="AN0183979959-27">DISCUSSION</hd> <p>Firstly, this Delphi Study focused on current and potential assessment of learning potential for children with moderate to severe intellectual disabilities. Findings showed that the value of dynamic testing using analogical reasoning tasks was broadly endorsed. If such a test would become available and would be in reach for children with moderate to severe intellectual disabilities, this would fill an important gap in current practice. These findings align with evidence from previous research that dynamic testing may be a promising tool to bridge the gap between assessment and educational practice (Bosma & Resing, [<reflink idref="bib7" id="ref70">7</reflink>]; Tiekstra et al., [<reflink idref="bib44" id="ref71">44</reflink>]).</p> <p>Secondly, the Delphi panel reached consensus on a conceptual definition of learning potential. Learning potential was defined as 'what a child can learn and apply in terms of new knowledge and skills, with appropriate help, instruction, and time.' This definition aligns with the previous definitions (e.g. Resing, [<reflink idref="bib34" id="ref72">34</reflink>]) of learning potential as the maximum progress a learner can make in an ideal learning situation. Our operational definition added concrete parameters that such tests should include. Experts agreed that dynamic testing of learning potential of children with moderate to severe intellectual disabilities should involve a pre‐test, training, post‐test structure with a graduated prompts protocol and an observation checklist (observing the response to mediation of the child).</p> <p>Thirdly, based on the example of the ARLT, several adaptations in test design were assessed as being relevant. Adjustment of difficulty levels by adapting the materials and the content of the tasks were deemed necessary. For children with severe intellectual disabilities, the participating experts questioned the ability of these children to achieve the adapted tasks and advised further research on this matter. Also, the experts emphasized that children with moderate to severe intellectual disabilities would need more time than usual for dynamic testing, allowing them to process instructions and show their learning potential. The length of the training phase should provide enough time for a child to learn from instruction but also consider practical usability and thus avoiding a too long and time‐consuming training.</p> <p>The Delphi panel agreed that a protocol of graduated prompts based on Visser et al. ([<reflink idref="bib50" id="ref73">50</reflink>]) would tailor training to children's needs and obtain reliable outcomes. Standardization of the training enhances replicability of results, allows responses of different children to be compared, and diminishes the influence of personal characteristics of the examiner, which are important criteria for dynamic test development. The use of graduated prompts was found to be an effective training method in previous studies (Resing & Elliott, [<reflink idref="bib37" id="ref74">37</reflink>]; Stevenson et al., [<reflink idref="bib42" id="ref75">42</reflink>]). Further research on the training of cognitive skills for children with moderate to severe intellectual abilities may be needed to gain consensus on the best suited training period and the development of an effective protocol of graduated prompts. This will be a major topic and next step in our research project.</p> <p>Fourthly, both quantitative measures and qualitative information may be helpful to tailor educational support (Tiekstra et al., [<reflink idref="bib44" id="ref76">44</reflink>]). The connection between outcomes of dynamic testing and personalized educational support has been the subject of research (e.g. Lauchlan, [<reflink idref="bib28" id="ref77">28</reflink>]). It is assumed, but rarely tested, that results from dynamic testing can be generalized to learning in the classroom (Jeltova et al., [<reflink idref="bib27" id="ref78">27</reflink>]). However, linking outcomes to meaningful educational interventions is crucial for a wider use of dynamic testing in psychological educational assessment (Elliott, [<reflink idref="bib17" id="ref79">17</reflink>]; Lauchlan, [<reflink idref="bib28" id="ref80">28</reflink>]). Participants in our study emphasized the relevance of this connection and commented that it may be more valuable to know what and how a child would be able to learn than to classify and quantify high or low learning potential. This aligns with Elliott ([<reflink idref="bib16" id="ref81">16</reflink>]) who stated that clinicians may only consider dynamic assessment worthwhile if greater emphasis is placed upon informing intervention than on classification and selection. Further research in how this can be done in a meaningful and reliable way is considered necessary.</p> <p>Finally, optimal learning requires that the educational context and the instruction offered match the abilities and educational needs of children (Thompson et al., [<reflink idref="bib43" id="ref82">43</reflink>]). A continuous mutual interaction between the child, teacher/supervisor, and learning environment is essential for optimal learning to take place. From this perspective, the concepts of learning potential and dynamic testing can also be considered 'tricky' concepts. If the educational environment is not adequately tailored to the educational needs of a child, the prediction of poor learning potential will become a self‐fulfilling prophecy (Bosma & Resing, [<reflink idref="bib6" id="ref83">6</reflink>]; Elliott, [<reflink idref="bib17" id="ref84">17</reflink>]). This raises some important issues that require further consideration. If after training no progress in learning is measured, one might wrongly conclude that the child has no learning potential instead of concluding that the specific training used in the test does not lead to learning and the child may need other forms of support. Also, previous research (e.g. Bosma & Resing, [<reflink idref="bib7" id="ref85">7</reflink>]) indicated that feeding back the results of dynamic testing to parents, teachers and/or supervisors might influence their expectations which could lead to offering less support and learning opportunities if they expect less learning progress, which may lead to a self‐fulfilling prophecy.</p> <hd id="AN0183979959-28">LIMITATIONS</hd> <p>A possible limitation of this study might be bias in the selection of participants. It is plausible that mostly people with a particular interest in the subject of dynamic testing agreed on participating in the study. However, a broad variety of expertise was included, covering the whole field of psychological assessment in special schools and specialized day‐care. Also, the high consensus rates indicate that data saturation was likely obtained. Finally, in the Delphi study, only experts currently working in special schools and/or specialized day‐care in the Netherlands participated. The results of our study reflect consensus of opinions within these contexts; therefore, caution is required in generalizing results.</p> <hd id="AN0183979959-29">CONCLUSION</hd> <p>With the limitations considered, this study indicates that dynamic testing using analogical reasoning may be valuable alternative for children with moderate intellectual disabilities who attend special schools or specialized day‐care centres. For children with severe intellectual disabilities some questions remain, and further research is needed. The consensus‐based conceptual and operational definitions and the described test design requirements may provide guidance for the further development of a dynamic testing tool and trialling this in a feasibility study. The Delphi panel formulated some essential questions that should be included in such a study, for example, the optimal length of a training phase and the type of mediation suitable to guide the learning process of these children.</p> <hd id="AN0183979959-30">FUNDING INFORMATION</hd> <p>This study was funded by ZonMw (Grant number 641001103) and Stichting Wetenschappelijk Onderzoek of 's Heeren Loo.</p> <hd id="AN0183979959-31">CONFLICT OF INTEREST STATEMENT</hd> <p>No potential conflict of interest was reported by the authors.</p> <hd id="AN0183979959-32">DATA AVAILABILITY STATEMENT</hd> <p>The data that support the findings of this study are available on request from the corresponding author. 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  Data: Dynamic Testing of Learning Potential of Children with Moderate to Severe Intellectual Disabilities: A Delphi Study
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  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22M%2E+L%2E+Eding%22">M. L. Eding</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-9357-2184">0000-0002-9357-2184</externalLink>)<br /><searchLink fieldCode="AR" term="%22M%2E+Meeter%22">M. Meeter</searchLink><br /><searchLink fieldCode="AR" term="%22C%2E+Schuengel%22">C. Schuengel</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Journal+of+Research+in+Special+Educational+Needs%22"><i>Journal of Research in Special Educational Needs</i></searchLink>. 2025 25(1):32-43.
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  Label: Availability
  Group: Avail
  Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
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  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 12
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2025
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Delphi+Technique%22">Delphi Technique</searchLink><br /><searchLink fieldCode="DE" term="%22Moderate+Intellectual+Disability%22">Moderate Intellectual Disability</searchLink><br /><searchLink fieldCode="DE" term="%22Severe+Intellectual+Disability%22">Severe Intellectual Disability</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Child+Care+Centers%22">Child Care Centers</searchLink><br /><searchLink fieldCode="DE" term="%22Special+Schools%22">Special Schools</searchLink><br /><searchLink fieldCode="DE" term="%22Check+Lists%22">Check Lists</searchLink><br /><searchLink fieldCode="DE" term="%22Task+Analysis%22">Task Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Psychological+Testing%22">Psychological Testing</searchLink><br /><searchLink fieldCode="DE" term="%22Testing%22">Testing</searchLink><br /><searchLink fieldCode="DE" term="%22Specialists%22">Specialists</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Assessment%22">Educational Assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Preschool+Children%22">Preschool Children</searchLink><br /><searchLink fieldCode="DE" term="%22Logical+Thinking%22">Logical Thinking</searchLink>
– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Netherlands%22">Netherlands</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1111/1471-3802.12706
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1471-3802
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Education of children with moderate to severe intellectual disabilities requires adequate assessment of their educational needs and potential to learn. Dynamic testing using analogical reasoning tasks may be a promising way to perform such an assessment. However, it remains unclear how dynamic testing with these children may be done in practice. Therefore, we sought expert opinions on operationalizing learning potential and dynamic testing. We performed a three-round online Delphi study (N = 37) with experts in psychological educational assessment of children with moderate to severe intellectual disabilities in special schools and specialized day-care centres in the Netherlands. Consensus was found on a conceptual and an operational definition of learning potential, describing step-by-step how learning potential could be measured in daily practice. This included a pre-test, training, post-test design with the inclusion of a graduated prompts protocol for mediation and an observation checklist focussing on response to mediation. Based on examples from the Analogical Reasoning Learning Test, we assessed consensus on adapted design requirements for dynamic testing using analogical reasoning. Experts agreed that dynamic testing using analogical reasoning tasks might be suitable for children with moderate intellectual disabilities. A key concern was whether performance on analogical reasoning task was within reach of children with severe intellectual disabilities. The panel recommended research into the type of mediation needed to support the learning of analogical reasoning tasks. Further development and evaluation of dynamic testing for children with moderate to severe intellectual disabilities may build on the recommendations of this panel of experts.
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  Data: As Provided
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  Label: Entry Date
  Group: Date
  Data: 2025
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1456695
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        Value: 10.1111/1471-3802.12706
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      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 12
        StartPage: 32
    Subjects:
      – SubjectFull: Delphi Technique
        Type: general
      – SubjectFull: Moderate Intellectual Disability
        Type: general
      – SubjectFull: Severe Intellectual Disability
        Type: general
      – SubjectFull: Foreign Countries
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      – SubjectFull: Child Care Centers
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      – SubjectFull: Special Schools
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      – SubjectFull: Psychological Testing
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      – SubjectFull: Testing
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      – SubjectFull: Specialists
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      – SubjectFull: Educational Assessment
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      – SubjectFull: Preschool Children
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      – SubjectFull: Logical Thinking
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      – SubjectFull: Netherlands
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      – TitleFull: Dynamic Testing of Learning Potential of Children with Moderate to Severe Intellectual Disabilities: A Delphi Study
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