Educational PsychologyOrganizational PsychologyPsychometrics

Feedback Instrument for Rescue Force Development – Group work (FIRE-G)

The Feedback Instrument for Rescue Force Development – Group work (FIRE-G) is a validated 3-item psychological measurement instrument designed to assess learning-conducive peer interactions during collaborative group exercises in emergency service training.

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PUBLISHED
Scientifically Reviewed · Dr. Marwa Abd-Alazim · September 30, 2026
Medically & Scientifically Reviewed Verified: September 30, 2026
Dr. Marwa Abd-Alazim Ph.D.
Professor of Psychology • University of Kerbala
Review Criteria & Clinical Standards

This content undergoes rigorous scientific peer-review and medical editorial standards at Arab Psychology Network to ensure clinical accuracy, validity, and compliance with evidence-based guidelines from leading psychological and healthcare authorities (APA / WHO).

Abstract

The Feedback Instrument for Rescue Force Development – Group work (FIRE-G) is a standardized, psychometrically validated evaluation instrument designed to measure the perceived quality of collaborative learning and peer interactions during group work exercises in emergency service training. Developed as a specialized modular extension to the broader Feedback Instrument for Rescue Force Development (FIRE; Schulte & Thielsch, 2019; Schulte et al., 2019), the FIRE-G addresses the specific pedagogical dynamics of cooperative problem-solving among rescue forces, including firefighters, incident commanders, disaster response personnel, and emergency medical service leaders. The scale operationalizes the unidimensional construct of learning-conducive peer interactions (cooperative learning dynamics) using an ultra-brief three-item format administered via paper-and-pencil or computer-assisted systems. The instrument was developed and validated across multiple empirical samples totaling over 600 emergency personnel at the Institute of the North Rhine-Westphalia Fire Brigade (Institut der Feuerwehr Nordrhein-Westfalen; IdF NRW). In the primary validation cohort (N = 375), confirmatory factor analysis (CFA) demonstrated excellent structural fit for an essentially tau-equivalent unidimensional model (χ²(2) = 2.95, p = .229, CFI = .998, TLI = .997, RMSEA = .04, SRMR = .04). Internal consistency reliability proved robust across cohorts, yielding Cronbach’s α = .83 and McDonald’s ω = .83 in the primary validation study, and McDonald’s ω = .77 in an initial exploratory cohort (N = 240). Convergent and discriminant construct validity analyses confirmed substantial alignment with general peer group appraisal (r = .53 with the FIRE Group scale) and functional divergence from practical tactical exercises (FIRE-E), instructor demeanor, cognitive entry prerequisites, and momentary emotional bias. With an average administration time of approximately one minute, the FIRE-G provides educational practitioners, occupational psychologists, and emergency training organizations with an efficient, reliable, and construct-clean metric for didactic course optimization and pedagogical research.

Keywords

FIRE-G, rescue forces, firefighter training, group work evaluation, cooperative learning, didactic evaluation, emergency services, psychometrics, peer interaction, instructional quality, scale validation

Authors

The Feedback Instrument for Rescue Force Development – Group work (FIRE-G) was developed through an institutional research partnership between the Department of Organizational and Business Psychology at the University of Münster (Westfälische Wilhelms-Universität Münster) and the Institute of the North Rhine-Westphalia Fire Brigade (Institut der Feuerwehr Nordrhein-Westfalen, IdF NRW) in Münster, Germany.

  • Meinald T. Thielsch, PhD – Professor of Psychology, Department of Organizational and Business Psychology, Institute of Psychology, University of Münster, Münster, Germany.
  • Collaborating Researchers and Contributors – Associated research staff and instructional development personnel of the IdF NRW and the University of Münster, including authors of the modular FIRE framework (e.g., F. Schulte, K. Röseler, H. Kleinstück, and project associates).
  • Institutional Affiliation – Westfälische Wilhelms-Universität Münster, Fliednerstraße 21, 48149 Münster, Germany; Website: go.wwu.de/fire.

Purpose

The vocational demands placed upon rescue forces—such as professional and volunteer firefighters, technical relief specialists, and incident command officers—require a sophisticated integration of technical expertise, physical sciences, tactical doctrine, emergency medicine, and statutory legal frameworks. When deployed during critical incidents, commanding officers operate in dynamic, volatile, high-stakes environments where they must make rapid, consequential tactical decisions under severe time constraints. In such high-tempo crisis operational scenarios, commanders cannot readily pause to consult field manuals, legal compendiums, or external subject-matter experts. Consequently, theoretical classroom education and pedagogical preparation within modern fire academies and crisis training centers represent a vital, life-critical component of emergency force readiness.

Within adult vocational instruction and leadership development, group work stands as a core instructional method (teaching method) alongside plenary lecture instruction, independent study, and paired exercises (Drumm & Scholz, 2007). In emergency services leadership courses, collaborative group work exercises are routinely implemented to train officers in analyzing operational case studies, dissecting fire safety legislation, interpreting complex building codes, and formulating multi-agency response strategies. Despite the widespread use of small-group assignments, evaluating the efficacy and didactic quality of group work has historically suffered from methodological conflation. In traditional end-of-course student evaluations of teaching (SET), items assessing small-group activities are frequently intermixed with instructor facilitation, administrative clarity, or general physical logistics.

The primary purpose of the FIRE-G is to isolate and measure the educational quality of small-group collaborative processes from the perspective of course participants. Rather than evaluating whether the lecturer was engaging or whether the classroom supplies were adequate, the FIRE-G assesses the degree to which peer-to-peer interactions generated a collaborative learning climate characterized by reciprocal knowledge construction, competent and equitable contribution, and active dialogue. By decoupling instructional group interactions from direct lecturer behaviors, the scale fills an essential gap in instructional feedback systems.

In applied training environments, the FIRE-G serves multiple operational functions:

  • Curricular and Didactic Optimization: Course designers and instructors receive granular, targeted feedback regarding whether specific small-group modules succeeded in fostering peer exchange, enabling instructors to adapt task structure, group size, or preparation materials.
  • Instructor-Student Reflection Dialogues: Aggregate scores serve as an objective basis for instructional debriefings (Evaluationsbesprechungen), where instructors and adult learners jointly examine what worked well and what collaborative barriers emerged.
  • Benchmarking Across Instructional Designs: Training academies can compare alternative pedagogical methodologies (e.g., structured jigsaw classrooms versus open case discussions) across different cohorts and course iterations.
  • Empirical Educational and Organizational Research: The scale enables occupational and educational psychologists to model the structural relationships linking collaborative learning dynamics to course satisfaction, leadership competence acquisition, and real-world transfer to emergency field operations.

Psychological Construct

The psychological construct captured by the FIRE-G is learning-conducive peer interaction (lernförderliche Interaktionen) within small-group instructional settings. Rooted in social-constructivist and cooperative learning theories, this construct conceptualizes collaborative learning not merely as passive co-presence or logistical group division, but as active sociocognitive engagement among adult learners.

Learning-conducive interactions encompass three core interrelated operational facets:

1. Reciprocal Peer Learning and Knowledge Construction

Adult learners in emergency leadership courses bring diverse experiential backgrounds from municipal career departments, volunteer fire stations, industrial plants, and emergency medical agencies. When an instructional task functions effectively, participants engage in cognitive elaboration: they articulate tacit knowledge, explain tactical reasoning to peers, justify operational decisions, and encounter alternative problem-solving strategies (Renkl, 2015). This active sociocognitive processing prompts cognitive conflict, exposes individual knowledge gaps, and leads to refined conceptual schemas. The FIRE-G directly measures this subjective gain through item reflections on how much the participant acquired knowledge directly from fellow trainees (Item 1).

2. Equitable Competence-Based Participation and Social loafing Mitigation

A persistent vulnerability in collaborative group work is the emergence of dysfunctional group dynamics, specifically social loafing or free-riding (Karau & Williams, 1993), wherein individual group members withhold effort when personal accountability is diffuse. A related phenomenon is the sucker effect (Gimpel-Effekt; Schnake, 1991), wherein highly motivated members reduce their own contributions to avoid being exploited by unengaged peers. In an optimal collaborative group setting, participants participate proportionally in alignment with their specialized individual competencies, skills, and background knowledge. The FIRE-G operationalizes this cooperative norm through Item 2, assessing the degree to which every member actively contributed according to their individual competence.

3. Facilitated Multidirectional Discourse and Peer Exchange

Effective small-group work requires an interactive architecture that stimulates multidirectional discourse rather than parallel, isolated individual work. Group assignments must prompt dialogue, debate, collaborative negotiation, and shared consensus building regarding operational tactics and statutory mandates. The third facet of the construct captures the extent to which the group task catalyzed vibrant interpersonal exchange and discourse among the trainees (Item 3).

Importantly, during the psychometric refinement of the FIRE-G, the authors deliberately excluded items reflecting external administrative or instructor variables (such as clarity of task instructions, adequacy of instructor coaching during group exercises, and plenary debriefing). By removing these confounding logistical aspects, the construct was purified into an unconfounded assessment of internal group communicative synergy and sociocognitive learning exchange.

Theoretical Framework

The theoretical architecture of the FIRE-G rests upon established principles of educational psychology, social psychology of groups, and adult vocational learning paradigms.

Sociocognitive Interaction and Knowledge Elaboration

According to social constructivist educational theory (e.g., Vygotsky, 1978; Renkl, 2015), high-level learning occurs when individuals actively construct cognitive schemas through mediated interaction with their social environment. Within classroom settings, group work serves as one of four fundamental social arrangements, alongside individual work, dyadic partner work, and frontal plenary lecturing (Drumm & Scholz, 2007). In small-group settings, adult learners do not merely absorb information passively; they are compelled to explicate their line of thought, explain abstract operational rationales to peers, debate ambiguous edge cases, and justify tactical maneuvers. This process of verbal explication forces the learner to organize internal mental models systematically. As highlighted by Renkl (2015), when peers present conflicting perspectives or identify flaws in an argument, the learner experiences cognitive dissonance, which drives deeper information processing and long-term retention.

Phases of Group Work in Emergency Vocational Training

In high-reliability training environments such as the fire service, group exercises follow structured pedagogical trajectories. Pluntke (2013) conceptualizes instructional group work across three distinct, consecutive phases:

  1. The Task Briefing Phase (Auftragsphase): The instructor delivers an explicit verbal or written operational assignment (e.g., developing a hazardous material containment strategy or applying administrative fire safety regulations to a public building). Precise task constraints are critical for functional group operation.
  2. The Autonomous Working Phase (Arbeitsphase): The group works independently without direct instructor interference. The lecturer steps into the background, assuming the role of a passive resource person available for clarifying technical questions if summoned, while the group negotiates its own working processes and intermediate deadlines.
  3. The Plenary Debriefing Phase (Auswertungsphase): The groups reconvene in the plenary lecture hall to present their syntheses, compare solutions across teams, and receive structured feedback moderated by the instructor.

Because the second phase represents the autonomous arena where trainees interact directly with one another, the pedagogical success of the exercise hinges entirely on group-level dynamics during this window.

Mitigating Dysfunctional Group Phenomena

The theoretical rationale for developing the FIRE-G also incorporates classic social-psychological models of collective effort. As demonstrated by Karau and Williams (1993) in their Collective Effort Model (CEM), individuals routinely exhibit social loafing when individual outputs are pooled and personal accountability diminishes. In training cohorts with wide age and experience discrepancies, social loafing can quickly trigger the sucker effect (Schnake, 1991), degrading the exercise into cynical disengagement. Pedagogical researchers emphasize that instructors can mitigate these dysfunctional phenomena by designing challenging, interdependent group tasks, keeping group sizes modest, and ensuring that assignments require the explicit mobilization of differentiated member competencies (Liden et al., 2004). The FIRE-G captures whether the resulting group execution successfully achieved this cooperative equilibrium.

Validity

The psychometric validity of the FIRE-G has been systematically demonstrated through empirical investigations assessing content validity, internal structural validity, and external construct validity (convergent and discriminant evidence).

Content Validity

Content validity was evaluated in Study I (N = 33), comprising seven senior fire academy instructors (86% male, mean age = 38.9 years, SD = 6.0) and 26 officer trainees enrolled in a certified fire incident commander course (Gruppenführer, 96% male, mean age = 30.5 years, SD = 6.9) at the Institute of the North Rhine-Westphalia Fire Brigade (IdF NRW). All participants conducted a rigorous review of candidate items evaluating instructional relevance and comprehensibility. With the exception of one initial item (G_5: “Trainees were interested in a good group work outcome”), which was rated important by only 76% of respondents and was subsequently revised into a first-person format, all proposed group work items achieved approval ratings exceeding 80% for instructional relevance. Furthermore, no item was deemed incomprehensible by more than 3% of the expert panel. Expert evaluations affirmed that the scale captures the essential facets of peer-driven collaborative learning.

Structural Construct Validity

Factorial validity was established across two independent cohorts. In Study II (N = 240), an exploratory factor analysis (EFA) demonstrated strong single-factor saturation for the interaction-focused items, with factor loadings ranging from .81 to .84. In Study III (N = 375), confirmatory factor analysis (CFA) formally tested the single-factor structural representation. Using maximum likelihood estimation with robust standard errors (MLR), an essentially tau-equivalent unidimensional model yielded an excellent fit to the empirical data (χ²(2) = 2.95, p = .229, CFI = .998, TLI = .997, RMSEA = .04, 90% CI [.00, .12], SRMR = .04). A chi-square difference test confirmed that constraining factor loadings to equality (tau-equivalence) did not significantly degrade model fit compared to an unconstrained congeneric model (Δχ²(2) = 2.95, df = 2, p = .229), empirically validating the interchangeable weighting of items in composite scoring.

Convergent Validity

Convergent construct validity was examined in Study III by correlating the FIRE-G composite with validated subscales from the comprehensive FIRE core questionnaire (Schulte & Thielsch, 2019). The FIRE-G exhibited a strong, statistically significant positive correlation with the FIRE Group scale (r = .53, p < .001, n = 373). Because the FIRE Group subscale assesses general social cohesion and mutual support across the entire course cohort, this substantial correlation verifies that the FIRE-G captures relevant peer interaction dynamics while focusing specifically on collaborative task performance.

Discriminant Validity

Discriminant validity was established through several planned comparisons:

  • Contrast with Practical Scenario Exercises (FIRE-E): While group work in theoretical courses revolves around discussion, negotiation, and cognitive problem-solving, practical tactical command exercises (Einsatzübungen) involve physical drills and rapid operational commands under simulated stress. Correlating the FIRE-G with the FIRE-E module (Röseler et al., 2020) demonstrated a moderate, differentiated relationship, reflecting that practical exercises share group characteristics but test distinct operational modalities.
  • Differentiation from Instructor Demeanor: By purposely excluding instructor support and debriefing items during scale refinement, the FIRE-G was structurally separated from lecturer-focused evaluations. Consequently, the FIRE-G correlates distinctly lower with the FIRE Instructor Behavior (Dozentenverhalten) scale than it does with peer-focused scales.
  • Independence from Cognitive Entry Prerequisites: The correlation between FIRE-G scores and trainee scores on the objective standardized course entry examination (Eingangsprüfung) was non-significant. This establishes that prior theoretical knowledge and entry test preparation do not bias trainees’ post-course appraisals of group work quality.
  • Control for Subjective Mood Bias: In instructional evaluation, student mood constitutes a recognized bias variable (Spiel, 2001) that can artificially inflate ratings. Trainee mood was assessed using a five-point smiley visual analog scale (Jäger, 2004). The FIRE-G exhibited only a minor correlation with momentary mood, confirming that the scale captures substantive instructional properties rather than momentary affective states.

Reliability

The reliability of the FIRE-G was thoroughly evaluated across independent samples using classical test theory and structural equation modeling frameworks.

Internal Consistency Across Validation Cohorts

Because the FIRE-G contains three items, evaluating its internal consistency requires precise alignment with the underlying measurement model:

  • Study II Cohort (N = 240): In this sample of incident command trainees (95.4% male, mean age = 31.8 years, SD = 6.5; 13.7 mean years of service), a tau-congeneric measurement model was identified (Δχ²(2) = 6.91, p = .032). Under congeneric assumptions, McDonald’s ω serves as the appropriate, unattenuated reliability coefficient. The scale yielded a McDonald’s ω of .77, indicating satisfactory internal consistency for an ultra-brief three-item scale in exploratory testing.
  • Study III Cohort (N = 375): In the definitive validation sample of officer course participants (93.9% male, mean age = 33.4 years, SD = 6.8; 14.4 mean years of operational experience), an essentially tau-equivalent model was established (Δχ²(2) = 2.95, p = .229). Under conditions of essential tau-equivalence (equal factor loadings), Cronbach’s α is an exact and unbiased estimator of internal consistency. The FIRE-G achieved a Cronbach’s α of .83 and an identical McDonald’s ω of .83.

An internal consistency coefficient of .83 for a three-item metric is exceptionally high, demonstrating that the items tap into a unified, coherent psychological dimension without introducing excessive item redundancy.

Factor Analysis

The factorial validity of the FIRE-G was examined across two sequential empirical phases: initial item reduction via exploratory factor analysis (EFA) and subsequent model confirmation via confirmatory factor analysis (CFA).

Item Development and Exploratory Factor Analysis (Study II)

The original item battery comprised seven candidate items: four assessing peer learning interactions (G_1, G_3, G_5, G_6) and three assessing organizational/instructor facilitation (G_2: instructor support; G_4: debriefing quality; G_7: clarity of task instructions). Candidate item G_5 (“Participants cared about a good result”) exhibited marked ceiling effects and restricted variance (M = 6.14, SD = 0.82, kurtosis = 4.67) and was excluded prior to exploratory factor extraction.

An exploratory principal component analysis with oblimin rotation was conducted on the remaining six items (EFA 1; N = 240) using the R package psych (Revelle, 2021). All six items displayed substantial factor loadings ranging from .66 to .80 on a single general dimension, with item communalities (h²) ranging between .41 and .61. However, to preserve test economy and construct cleanliness, the authors removed items G_2, G_4, and G_7 because they indexed instructor-dependent organizational aspects already captured by other specialized tools (the FIRE core scale and the FIRE-DO instructor evaluation module; Kleinstück et al., 2021). A subsequent oblimin-rotated EFA on the three peer-focused items (EFA 2) revealed clean, exceptionally high factor loadings:

  • Item G_1: Loading = .83, h² = .68 (Corrected item-total correlation rit = .57)
  • Item G_3: Loading = .84, h² = .76 (Corrected item-total correlation rit = .67)
  • Item G_6: Loading = .81, h² = .65 (Corrected item-total correlation rit = .63)

Confirmatory Factor Analysis (Study III)

In Study III (N = 375), the structural integrity of the final three-item configuration was formally tested via CFA using the R package lavaan (Rosseel, 2012) with robust maximum likelihood (MLR) estimation. Because a standard congeneric model with three manifest indicators has exactly zero degrees of freedom (df = 0)—representing a just-identified model wherein goodness-of-fit indices cannot be mathematically calculated—the authors applied an essentially tau-equivalent specification. In an essentially tau-equivalent model, unstandardized factor loadings are constrained to equality while error variances remain freely estimated, yielding two degrees of freedom (df = 2; Czerwiński & Atroszko, 2021).

The resulting CFA demonstrated outstanding fit to the empirical data:

  • χ²(2) = 2.95, p = .229
  • Comparative Fit Index (CFI) = .998
  • Tucker-Lewis Index (TLI) = .997
  • Root Mean Square Error of Approximation (RMSEA) = .04, 90% CI [.00, .12]
  • Standardized Root Mean Square Residual (SRMR) = .04

Following the standard fit criteria established by Hu and Bentler (1999), these results confirm an exemplary structural representation of the construct.

Item Characteristics in the Validation Sample

Descriptive statistics and psychometric properties for the manifest items in Study III (N = 375) are presented below:

  • Item 1 (G_1): M = 5.36, SD = 1.13, Skewness = -1.03, Kurtosis = 1.52, Corrected Item-Total Correlation (rit) = .69
  • Item 2 (G_3): M = 5.68, SD = 1.02, Skewness = -1.43, Kurtosis = 3.16, Corrected Item-Total Correlation (rit) = .71
  • Item 3 (G_6): M = 5.77, SD = 1.03, Skewness = -1.19, Kurtosis = 1.60, Corrected Item-Total Correlation (rit) = .67

All items demonstrate strong discriminatory power (all rit ≥ .67) and acceptable distribution parameters typical of positive training evaluations.

Instrument / Measurement Tool

  • Instrument Name: Feedback Instrument for Rescue Force Development – Group work (FIRE-G) / Feedback-Instrument zur Rettungskräfte-Entwicklung – Gruppenarbeit
  • Type of Test: Standardized self-report instructional evaluation instrument / Modular educational survey
  • Administration Format: Paper-and-Pencil Assessment (PASI / PAPI) or Computer-Assisted Web Interview (CAWI / Online survey)
  • Number of Items: 3 items (unidimensional)
  • Estimated Completion Time: Approximately 1 minute (60 seconds)
  • Target Population: Trainees, officers, and leaders in emergency rescue services, fire brigades, disaster response units, and related vocational and higher education contexts
  • Authentic Response Scale: 7-point Likert-type response scale:
    • 1 = stimme gar nicht zu (strongly disagree)
    • 2 = stimme nicht zu (disagree)
    • 3 = stimme eher nicht zu (somewhat disagree)
    • 4 = neutral (neutral)
    • 5 = stimme eher zu (somewhat agree)
    • 6 = stimme zu (agree)
    • 7 = stimme vollkommen zu (strongly agree)
    • Additional option: nicht sinnvoll beantwortbar (cannot be meaningfully answered / not applicable)
  • Scoring and Computational Rules:
    • Point Allocation: Responses receive integer points from 1 (stimme gar nicht zu) to 7 (stimme vollkommen zu). All three items are positively poled (no reverse coding required).
    • Handling of Non-Applicable / Missing Responses: The option “nicht sinnvoll beantwortbar” receives no numeric points and is treated as missing data for that respondent. In online administrations, items should be set as mandatory prompts with the non-applicable box available. In paper-and-pencil surveys, respondents with one or more omitted items are excluded from aggregated cohort statistics.
    • Individual Scale Score (Research Purposes): Sum the points of the valid answered items and divide by the number of completed items (mean score ranging from 1.0 to 7.0).
    • Course Evaluation Scale Score (Aggregated Course Feedback):
      1. Calculate the unweighted arithmetic mean for each individual item across all respondents who answered that item: Item_Mean = ∑(Item_Points) / N_respondents.
      2. Sum the three item means and divide by 3 to produce the final overall FIRE-G evaluation metric: Scale_Mean = (Item_Mean_1 + Item_Mean_2 + Item_Mean_3) / 3.
  • Interpretation Guidelines: Higher scores reflect higher perceived didactic quality and more learning-conducive peer interaction during group assignments. Normative benchmark averages from fire officer leadership courses typically fall between 5.36 and 5.77 on the 7-point scale. To protect respondent anonymity, evaluations should only be analyzed and reported if a minimum of 8 completed questionnaires are submitted (or at least 50% participation in small cohorts of 10 to 14 participants; Thielsch & Weltzin, 2013).

Permissions & Fee and Test Year

  • Development and Publication Year: Developed and validated between 2015 and 2017; published within the FIRE modular instrument series (Schulte & Thielsch, 2019; Schulte et al., 2019).
  • Copyright and Intellectual Property: © Meinald T. Thielsch and the authors, Westfälische Wilhelms-Universität Münster & Institut der Feuerwehr NRW.
  • Licensing and Accessibility: The FIRE-G scale items and instructional modules are made freely available for non-commercial academic research, institutional evaluation, and educational quality management purposes. Academies, universities, and emergency services organizations may administer the questionnaire without license fees.
  • Access URL: Official scale repository, documentation, and digital modules can be accessed at go.wwu.de/fire.

References

  • Czerwiński, S. K., & Atroszko, P. A. (2021). A solution to the problem of unidentified three-item confirmatory factor analysis models in scale validation. Current Problems of Psychiatry, 22(3), 133–144. https://doi.org/10.2478/cpp-2021-0013
  • Drumm, H. J., & Scholz, C. (2007). Personalmanagement (6th ed.). Springer.
  • Grötemeier, I., & Thielsch, M. T. (2014). Evaluationsbericht zur Lehre am Institut der Feuerwehr NRW. WWU Münster.
  • Hu, L. t., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
  • Jäger, R. S. (2004). Von der Beobachtung zur Notengebung: Ein praxisorientiertes Handbuch zur Leistungsbeurteilung in der Schule (4th ed.). Empirische Pädagogik.
  • Karau, S. J., & Williams, K. D. (1993). Social loafing: A meta-analytic review and theoretical integration. Journal of Personality and Social Psychology, 65(4), 681–706. https://doi.org/10.1037/0022-3514.65.4.681
  • Kleinstück, H., Schulte, F. P., & Thielsch, M. T. (2021). Evaluation von Dozierenden im Rettungswesen – Das FIRE-DO. Zeitschrift für Arbeits- und Organisationspsychologie, 65(3), 170–182. https://doi.org/10.1026/0932-4089/a000356
  • Liden, R. C., Wayne, S. J., Jaworski, R. A., & Bennett, N. (2004). Social loafing: A field investigation. Journal of Management, 30(2), 285–304. https://doi.org/10.1016/j.jm.2003.02.002
  • Niemann, B., & Thielsch, M. T. (2020). Evaluation in der Grundausbildung der Feuerwehr – Der Kernfragebogen FIRE-B. BrandSchutz – Deutsche Feuerwehr-Zeitung, 74(11), 844–847.
  • Pluntke, M. (2013). Methodenhandbuch für den Unterricht: Ein Praxisbuch für Lehrende an Schulen und Hochschulen. Carl Link Verlag.
  • Renkl, A. (2015). Kooperatives Lernen. In E. Wild & J. Möller (Eds.), Pädagogische Psychologie (2nd ed., pp. 85–104). Springer. https://doi.org/10.1007/978-3-642-41291-2_4
  • Revelle, W. (2021). psych: Procedures for Psychological, Psychometric, and Personality Research (R package version 2.1.9). Northwestern University. https://CRAN.R-project.org/package=psych
  • Röseler, K., Schulte, F. P., & Thielsch, M. T. (2020). Einsatzübungen systematisch evaluieren: Das Instrument FIRE-E. BrandSchutz – Deutsche Feuerwehr-Zeitung, 74(4), 254–259.
  • Röseler, K., Schulte, F. P., & Thielsch, M. T. (2021). Feedback-Instrument zur Rettungskräfte-Entwicklung – Einsatzübungen (FIRE-E). Zusammenstellung sozialwissenschaftlicher Items und Skalen (ZIS). https://doi.org/10.6102/zis294
  • Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36. https://doi.org/10.18637/jss.v048.i02
  • Schnake, M. E. (1991). Equity in effort: The sucker effect in co-acting groups. Journal of Management, 17(1), 41–55. https://doi.org/10.1177/014920639101700104
  • Schulte, F. P., & Thielsch, M. T. (2019). Lehrevaluation in der Führungsausbildung von Rettungskräften: Konstruktion und Validierung des Fragebogens FIRE. Zeitschrift für Arbeits- und Organisationspsychologie, 63(3), 143–158. https://doi.org/10.1026/0932-4089/a000297
  • Schulte, F. P., Wittmann, R., & Thielsch, M. T. (2019). Feedback-Instrument zur Rettungskräfte-Entwicklung (FIRE): Manual zum Kernfragebogen. WWU Münster & Institut der Feuerwehr NRW. https://doi.org/10.17879/85149692484
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  • Thielsch, M. T., & Hadzihalilovic, D. (2020). Ausbildung von Führungsstäben im Katastrophenschutz: Evaluation mit dem FIRE-CU. Bevölkerungsschutz, 2020(3), 33–35.
  • Thielsch, M. T., Niemann, B., & Schulte, F. P. (2019). Lehrevaluation in der Grundausbildung der Feuerwehr. Zeitschrift für Notfallwissenschaft und Notfallmanagement, 1(1), 12–18.
  • Thielsch, M. T., & Weltzin, S. (2013). Lehrevaluation an der Universität Münster: Ein Leitfaden für Lehrende und Fachbereiche. Zentrum für Hochschullehre, WWU Münster.
  • Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.

Items of the Scale

Instruktion:

Liebe/r Lehrgangsteilnehmer/in,

wir danken Ihnen, dass Sie an der Befragung teilnehmen! Indem Sie die Gruppenarbeiten bewerten, helfen Sie uns, die Qualität der Lehre in der Rettungskräfteausbildung zu beurteilen und gegebenenfalls zu verbessern. Bitte geben Sie an, wie sehr Sie den untenstehenden Aussagen zustimmen. Kreuzen Sie für jede Aussage das Kästchen an, das den Grad Ihrer Zustimmung am besten wiedergibt. Es gibt bei dieser Befragung keine richtigen oder falschen Antworten. Vielmehr interessieren wir uns für Ihre ganz persönliche Meinung.

Bitte beachten Sie:

  • Machen Sie hinter jeder Aussage jeweils nur ein Kreuz in einem der vorgesehenen Kästchen. Bitte lassen Sie keine Aussagen aus. Wenn eine Aussage für Sie nicht sinnvoll beantwortbar ist, können Sie uns dies durch ein Kreuz in dem entsprechenden Kästchen mitteilen.
  • Wenn Sie ein Kreuz ändern möchten, malen Sie das falsch markierte Kästchen vollständig aus und machen ein neues Kreuz an der gewünschten Stelle.

Ihre Teilnahme an der Befragung ist freiwillig. Zudem erfolgt die Befragung selbstverständlich anonym. Die Ergebnisse werden nur in gesammelter Form, das heißt beispielsweise in Form von Mittelwerten zurückgemeldet. Ein Rückschluss auf Ihre Person ist damit ausgeschlossen.

[Technischer Hinweis: Diese Instruktion wird nur gegeben, falls die Skala allein angewendet wird. Wird die Skala als Ergänzungsmodul an andere Fragebögen wie den FIRE angehangen, erfolgt keine separate Instruktion.]

Antwortformat (Response Scale):
Siebenstufiges Antwortformat mit den Optionen 1 = stimme gar nicht zu, 2 = stimme nicht zu, 3 = stimme eher nicht zu, 4 = neutral, 5 = stimme eher zu, 6 = stimme zu, 7 = stimme vollkommen zu. Ein zusätzliches Feld bietet die Möglichkeit anzugeben, dass das jeweilige Item nicht sinnvoll beantwortbar sei.

1. Ich habe bei den Gruppenarbeiten viel von anderen Teilnehmenden gelernt.

Optionen: 1 = stimme gar nicht zu | 2 = stimme nicht zu | 3 = stimme eher nicht zu | 4 = neutral | 5 = stimme eher zu | 6 = stimme zu | 7 = stimme vollkommen zu | [ ] nicht sinnvoll beantwortbar

2. Alle Teilnehmenden haben sich entsprechend ihrer Kompetenzen an den Gruppenarbeiten beteiligt.

Optionen: 1 = stimme gar nicht zu | 2 = stimme nicht zu | 3 = stimme eher nicht zu | 4 = neutral | 5 = stimme eher zu | 6 = stimme zu | 7 = stimme vollkommen zu | [ ] nicht sinnvoll beantwortbar

3. Die Gruppenarbeiten haben den Austausch zwischen den Teilnehmenden gefördert.

Optionen: 1 = stimme gar nicht zu | 2 = stimme nicht zu | 3 = stimme eher nicht zu | 4 = neutral | 5 = stimme eher zu | 6 = stimme zu | 7 = stimme vollkommen zu | [ ] nicht sinnvoll beantwortbar

Anmerkung: Alle Items sind positiv gepolt.

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Cite This Article

memjavad (2026, September 30). Feedback Instrument for Rescue Force Development – Group work (FIRE-G). PSYCHOLOGICAL DATABASE. https://en.arabpsychology.com/scales/feedback-instrument-for-rescue-force-development-group-work-fire-g/
memjavad. “Feedback Instrument for Rescue Force Development – Group work (FIRE-G).” PSYCHOLOGICAL DATABASE, 30 September 2026, https://en.arabpsychology.com/scales/feedback-instrument-for-rescue-force-development-group-work-fire-g/.
memjavad. “Feedback Instrument for Rescue Force Development – Group work (FIRE-G).” PSYCHOLOGICAL DATABASE. September 30, 2026. https://en.arabpsychology.com/scales/feedback-instrument-for-rescue-force-development-group-work-fire-g/.