The Feedback Instrument for Rescue Force Development \u2013 Exercises for independent work<\/strong> (commonly abbreviated as FIRE-EV<\/strong>, from the German Feedback-Instrument zur Rettungskr\u00e4fte-Entwicklung \u2013 Eigenverantwortliches Arbeiten<\/em>) is a standardized, psychometrically validated evaluation scale designed to assess the perceived pedagogical quality, structural adequacy, and didactic utility of autonomous learning tasks within rescue service and emergency leadership training. Conceptualized and validated through an institutional research collaboration between the Institute of the North Rhine-Westphalia Fire Brigade<\/a> (Institut der Feuerwehr Nordrhein-Westfalen<\/em>; IdF NRW) and the Department of Organizational and Business Psychology at the University of M\u00fcnster<\/a> (Westf\u00e4lische Wilhelms-Universit\u00e4t M\u00fcnster<\/em>), the instrument serves as a dedicated, modular extension to the broader FIRE core evaluation framework<\/strong> (Schulte & Thielsch, 2019; Schulte et al., 2019).<\/p>\n The scale consists of four unidimensional, positively worded items evaluated on a seven-point Likert-type response scale ranging from 1 (“strongly disagree”) to 7 (“strongly agree”), alongside an explicit non-substantive option (“cannot be meaningfully answered”). Psychometric validation conducted across diverse cohorts of operational incident commanders (e.g., group leaders [Gruppenf\u00fchrer<\/em>] and platoon leaders [Zugf\u00fchrer<\/em>]; cumulative calibration samples encompassing N<\/em> = 242 and N<\/em> = 364 emergency personnel) revealed an exemplary unidimensional factor structure via confirmatory factor analysis (\u03c7\u00b2(2) = 2.91, p<\/em> = .234, CFI = .998, TLI = .995, RMSEA = .04, SRMR = .01). The instrument demonstrates solid internal consistency across samples (Cronbach’s \u03b1 = .73 to .77; McDonald’s \u03c9 = .75 to .78) and strong evidence of construct, convergent, criterion-related, and discriminant validity. Empirical correlations verify robust associations with instructor behavior (r<\/em> = .51), self-reported competence acquisition (r<\/em> = .40), transfer of learning (r<\/em> = .39), and overall course satisfaction (r<\/em> = .50), while demonstrating theoretical divergence from general incoming pre-course test performance (r<\/em> = .03) and minimal confounding by concurrent affective mood states (r<\/em> = .25). The FIRE-EV provides an efficient, one-minute diagnostic instrument for instructional developers, emergency service academies, and educational researchers seeking to optimize independent learning paradigms in high-stakes training environments<\/span>.<\/p>\n FIRE-EV, rescue forces, emergency services, firefighter training, independent work, self-regulated learning, didactic evaluation, instructional quality, vocational education, confirmatory factor analysis, psychometrics, autonomous learning tasks<\/p>\n The FIRE-EV instrument was developed, calibrated, and validated through an academic-practitioner partnership between the Institute of the North Rhine-Westphalia Fire Brigade (IdF NRW) and the University of M\u00fcnster:<\/p>\n In high-reliability organizations (HROs) such as municipal fire departments, disaster management authorities, humanitarian medical units, and emergency rescue services, vocational education must satisfy demanding professional standards. Responders operating in command, tactical, and leadership positions are routinely required to make high-stakes, time-critical decisions under severe environmental stressors, extreme uncertainty, cognitive overload, and physical danger. The pedagogical curricula designed to prepare incident commanders must therefore impart a dense foundation of theoretical principles spanning engineering, fluid dynamics, chemistry, hazardous materials response, emergency medicine, civil protection doctrine, and administrative law. Because tactical command scenarios do not permit leaders to pause operations to consult textbooks, review checklists, or deliberate endlessly with staff, instructional curricula place heavy emphasis on theoretical mastery that can be rapidly mobilized into situational tactical decisions.<\/p>\n To cultivate these advanced professional competencies without overburdening classroom instructional hours, vocational training academies increasingly rely on asynchronous, self-directed learning modules\u2014known within German pedagogical traditions as Aufgaben zum eigenverantwortlichen Arbeiten<\/em> (EVA tasks; exercises for independent work). EVA assignments constitute structured, self-regulated individual tasks completed by trainees outside of formal lecture hours (e.g., in evening study periods during residential courses). Trainees autonomously analyze complex scenario vignettes, evaluate fire protection blueprints, calculate hydraulic delivery capacities, and determine tactical task-force allocations. Despite the ubiquity of these exercises, standardized psychometric evaluation instruments specifically dedicated to measuring the didactic quality, scope, cognitive challenge, and comprehensibility of independent study tasks in emergency training settings were historically non-existent.<\/p>\n The primary purpose of the FIRE-EV is to fill this psychometric gap by providing an objective, brief, theoretically grounded evaluation scale. The scale addresses four fundamental diagnostic and practical applications:<\/p>\n The construct assessed by the FIRE-EV is defined as the perceived pedagogical and instructional quality of exercises for independent work<\/strong> (Qualit\u00e4t von Aufgaben zum eigenverantwortlichen Arbeiten<\/em>). Grounded in didactic design principles and cognitive load paradigms, this construct conceptualizes independent learning exercises not as isolated work products, but as an interactive instructional mechanism whose educational efficacy depends on specific psychological and structural characteristics.<\/p>\n Within educational psychometrics, instructional quality during independent study is manifested across four interdependent operational facets, which converge into a unified latent construct within the FIRE-EV:<\/p>\n The first structural dimension reflects the participant’s appraisal of the task’s quantitative extent relative to available time constraints. In self-directed learning environments, excessive volume triggers cognitive exhaustion, strategic superficiality (e.g., skimming or copying solutions), and task aversion. Conversely, an insufficient scope fails to activate necessary cognitive elaboration strategies, leaving foundational concepts under-practiced. Adequacy of scope (measured via Item 1: “Der Umfang der EVA-Aufgaben war angemessen”<\/em>) reflects the equilibrium wherein the assigned workload matches the learners’ temporal resources and cognitive capacities.<\/p>\n The second facet assesses the degree to which independent exercises succeed in fostering meaningful cognitive processing rather than rote repetition. Drawing upon cognitive theories of knowledge acquisition, effective independent work must facilitate the consolidation of episodic classroom instruction into durable, flexible mental models. High perceived quality on this dimension (measured via Item 2: “Die EVA-Aufgaben haben mein Verst\u00e4ndnis der Inhalte weiter vertieft”<\/em>) signifies that the exercises provoked higher-order cognitive operations, such as schema integration, relational thinking, and the application of theoretical principles to simulated operational problems.<\/p>\n Self-directed learning tasks require high transparency of instructions because learners cannot immediately request clarification from a physically present instructor. Task ambiguity introduces extrinsic cognitive load, forcing learners to expend mental effort deciphering what is required rather than mastering the content. Clarity of task phrasing and unambiguous expectations (measured via Item 3: “Die Aufgabenstellungen der EVA-Aufgaben waren verst\u00e4ndlich”<\/em>) constitute a prerequisite for autonomous task engagement and self-efficacy.<\/p>\n The fourth facet assesses the balance between task demands and learner competencies. Aligned with Vygotskian perspectives on learning and Cs\u00edkszentmih\u00e1lyi’s flow model, optimal learning occurs when task challenges align with the upper boundary of learner capability. Tasks that are excessively difficult induce helplessness, cognitive overload, and academic demotivation; tasks that are overly simplistic induce boredom and cognitive disengagement. An appropriate difficulty level (measured via Item 4: “Der Schwierigkeitsgrad der EVA-Aufgaben war angemessen”<\/em>) ensures productive cognitive friction that sustains motivation while supporting progressive mastery.<\/p>\n The psychometric architecture of the FIRE-EV is anchored in three theoretical paradigms from instructional psychology, cognitive science, and educational sociology:<\/p>\n In classical instructional design frameworks, pedagogical interactions are categorized into four fundamental social forms<\/em> (Sozialformen des Unterrichts<\/em>): frontal\/direct instruction, partner work, cooperative group work, and individual work (Siemer, 2007; Ulrich, 2016). Individual work (Einzelarbeit<\/em>) serves the distinct psychological purpose of autonomous acquisition, cognitive synthesis, and deliberate consolidation of curriculum content. In military, paramilitary, and civil protection academies, individual study tasks bridge the gap between classroom theory and real-time operational simulation. Pluntke (2013) emphasizes that for independent work to succeed, instructional designers must meet three conditions: allocating sufficient time, providing unambiguous operational prompts, and precisely balancing difficulty to avoid under-challenge or overwhelming frustration.<\/p>\n Independent study tasks inherently operate within models of self-regulated learning<\/a> (e.g., Boekaerts, 1997; Zimmerman, 2000; Sitzmann & Ely, 2011). In an EVA scenario, the learner transitions from a passive consumer of information to an active executive controller of their cognitive, metacognitive, and motivational processes. Autonomous tasks require planning competence, sustained volitional control, dynamic self-monitoring, and diagnostic error recognition (Dietrich et al., 1999). When tasks lack pedagogical clarity or clear relevance, learners experience self-regulatory failure, manifested as academic procrastination, task abandonment, or superficial compliance (Ackerman & Gross, 2005). Conversely, well-designed independent tasks stimulate intrinsic motivation, prompt mastery-oriented self-reflection, and enhance objective academic performance, a pattern documented across secondary, tertiary, and professional education (Boekaerts, 1997; Sitzmann & Ely, 2011).<\/p>\n The structural composition of the FIRE-EV directly reflects the principles of Cognitive Load Theory<\/a> (Sweller et al., 1998; Paas et al., 2003). CLT posits that human working memory is strictly limited in bandwidth and duration when processing novel information. Total cognitive load consists of three components:<\/p>\n Within this framework, the FIRE-EV acts as a diagnostic sensor for cognitive load alignment. Item 3 (clarity of instructions) measures the successful minimization of extrinsic cognitive load; Item 1 (appropriate volume) and Item 4 (calibrated difficulty) ensure that intrinsic load remains within working memory capacity; and Item 2 (deepened understanding) confirms the successful activation of germane cognitive load.<\/p>\n The construct, criterion-related, and convergent validity of the FIRE-EV were systematically evaluated in a sequence of psychometric studies conducted at the Institute of the North Rhine-Westphalia Fire Brigade (IdF NRW), adhering to international psychometric conventions (Cohen, 1992; American Educational Research Association et al., 2014).<\/p>\n Initial item generation adapted validated items from the M\u00fcnster Evaluation Questionnaire Homework Module (M\u00fcnsteraner Fragebogen zur Evaluation \u2013 Zusatzmodul Hausaufgaben<\/em>; MFE-ZHa; Gr\u00f6temeier & Thielsch, 2014), supplemented by context-specific didactic formulations. In Study I, a panel of N<\/em> = 33 domain actors\u2014comprising seven certified senior instructors (86% male, mean age = 38.9 years, SD<\/em> = 6.0) and 26 operational commanders participating in advanced leadership training courses (96% male, mean age = 30.5 years, SD<\/em> = 6.9)\u2014critically reviewed the initial item pool. Participants rated each item on linguistic comprehensibility, professional relevance, and instructional importance. No EVA item was judged incomprehensible by more than 3% of the sample. Furthermore, items addressing scope, understanding, phrasing, and difficulty achieved exceeding endorsement, with over 90% of both instructors and participants rating them as “important” or “highly important” for learning success. Qualitative feedback confirmed that the four final core items comprehensively represented the quality dimensions of autonomous vocational exercises<\/span>.<\/p>\n To verify construct validity, the FIRE-EV was correlated with established dimensions of the overarching FIRE core questionnaire (Schulte & Thielsch, 2019) and associated instructional scales:<\/p>\n Criterion-related validity was corroborated through a significant inverse relationship with perceived instructional overload (\u00dcberforderung<\/em>, FIRE; r<\/em> = -.35, p<\/em> < .001). When independent tasks are calibrated in difficulty, clear in instruction, and reasonable in volume, trainees experience significantly less cognitive and emotional overwhelm during the course<\/span>.<\/p>\n Divergent validity was examined against objective baseline performance: scores achieved on the standardized entrance examination (Eingangspr\u00fcfung<\/em>) administered upon arrival at the academy. If the FIRE-EV merely reflected participants’ prior academic aptitude or pre-existing technical knowledge, it would correlate strongly with baseline examination scores. Instead, the observed correlation was virtually zero and statistically non-significant (r<\/em> = .03, p<\/em> = .655, n<\/em> = 221). This non-significant relationship demonstrates that the FIRE-EV measures the didactic quality of the instructional tasks within the course itself, independent of incoming trainee cognitive ability or operational background<\/span>.<\/p>\n Educational evaluations can be vulnerable to affective mood confounding (Spiel, 2001). Trainee mood was assessed simultaneously using a validated five-point smiley facial-expression rating scale (J\u00e4ger, 2004). The correlation between the FIRE-EV and concurrent participant mood was modest (r<\/em> = .25, p<\/em> < .001). Because successful, rewarding learning experiences naturally induce positive affect, a small-to-moderate association is theoretically consistent; the absence of a large correlation confirmed that the scale was not compromised by mood-state halo effects<\/span>.<\/p>\n The reliability of the FIRE-EV was examined across two independent samples of fire service command personnel, assessing internal consistency under different measurement model assumptions:<\/p>\n To determine the mathematically appropriate internal consistency metric, competitive nested model testing was performed using chi-square difference testing (\u0394\u03c7\u00b2):<\/p>\n Both coefficients demonstrate that the four-item FIRE-EV scale achieves solid reliability for an ultra-brief instrument:<\/p>\n Given the brevity of the scale (four items) and its intended application as an aggregated organizational feedback metric, internal consistency estimates exceeding .75 satisfy established psychometric standards for group-level evaluation and diagnostic research.<\/p>\n The latent structural integrity of the FIRE-EV was developed using exploratory factor analysis (EFA) and confirmed via confirmatory factor analysis (CFA) across separate participant cohorts.<\/p>\n In Study II, an initial pool of six candidate items was administered to N<\/em> = 242 course participants (after excluding 108 records due to withheld data-sharing consent, unengaged response sets, or incomplete data). Descriptive analysis revealed that Item EVA_6 (“Die EVA-Aufgaben wurden ausreichend nachbesprochen”<\/em> \/ debriefing of tasks) exhibited inadequate corrected item-total correlation (rit<\/sub><\/em> = .17), negative excess kurtosis (-1.15), and substantial floor effects (M<\/em> = 3.69, SD<\/em> = 1.79), prompting its exclusion prior to factor extraction<\/span>.<\/p>\n An exploratory principal component analysis with oblimin rotation was conducted on the remaining items using the 2. Keywords<\/h2>\n
3. Authors<\/h2>\n
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4. Purpose<\/h2>\n
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5. Psychological Construct<\/h2>\n
1. Curricular and Quantitative Scope Adequacy (Workload Balance)<\/h3>\n
2. Cognitive Elaboration and Deep Conceptual Understanding<\/h3>\n
3. Instructional Transparency and Task Comprehensibility<\/h3>\n
4. Calibrated Difficulty Level (Zone of Proximal Development)<\/h3>\n
6. Theoretical Framework<\/h2>\n
Didactic Social Forms and Autonomous Learning<\/h3>\n
Self-Regulated Learning (SRL) Theory<\/h3>\n
Cognitive Load Theory (CLT)<\/h3>\n
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7. Validity<\/h2>\n
Content Validity and Expert Review (Study I)<\/h3>\n
Construct and Convergent Validity (Study III, N<\/em> = 364)<\/span><\/h3>\n
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Criterion-Related and Divergent Validity<\/h3>\n
Assessment of Affective Bias<\/h3>\n
8. Reliability<\/h2>\n
Measurement Invariance and Model Assumptions<\/h3>\n
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Internal Consistency Coefficients<\/h3>\n
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9. Factor Analysis<\/h2>\n
Exploratory Factor Analysis (Study II)<\/h3>\n
psych<\/code> package in R (Revelle, 2021). The analysis extracted a distinct unidimensional factor explaining substantial variance. Factor loadings for all retained items were high (ranging from .70 to .76), with communalities (h\u00b2<\/em>) between .48 and .58:<\/p>\n\n
Confirmatory Factor Analysis (Study III)<\/h3>\n