Development and validity evidence investigation of a design for additive manufacturing self-efficacy scale

Abstract As additive manufacturing (AM) processes become ubiquitous in engineering and design, there has emerged the need for a workforce skilled in designing for AM (DfAM). Researchers have proposed educational interventions to train students in DfAM; however, few measures with sufficient validity...
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Autor*in:	Prabhu, Rohan [verfasserIn] Simpson, Timothy W. Miller, Scarlett R. Meisel, Nicholas A.

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	Design for additive manufacturing Design education Assessment Self-efficacy

Anmerkung:	© The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022

Übergeordnetes Werk:	Enthalten in: Research in engineering design - London : Springer, 1989, 33(2022), 4 vom: 12. Juli, Seite 437-453
Übergeordnetes Werk:	volume:33 ; year:2022 ; number:4 ; day:12 ; month:07 ; pages:437-453

Links:	Volltext

DOI / URN:	10.1007/s00163-022-00392-1

Katalog-ID:	SPR048039373

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520			\|a Abstract As additive manufacturing (AM) processes become ubiquitous in engineering and design, there has emerged the need for a workforce skilled in designing for AM (DfAM). Researchers have proposed educational interventions to train students in DfAM; however, few measures with sufficient validity evidence have been proposed to assess the effects of these educational interventions on student designers’ learning. In this paper, we present the development of a ten-item DfAM self-efficacy scale spanning the opportunistic and restrictive DfAM domains, as they relate to conceptual design (i.e., preliminary concept generation and selection). We tested the criterion-related validity of the scale by comparing students’ self-efficacy to their prior AM and DfAM experience. Additionally, we tested the construct validity of the scale through exploratory and confirmatory factor analyses. Students’ responses to the scale positively correlated with their prior experience in AM and DfAM, thereby lending criterion-related validity. Additionally, factor analyses reveal that students’ responses are composed of two dimensions: (1) opportunistic DfAM and (2) restrictive DfAM, reflecting the categorization observed in the literature. This finding lends construct validity evidence and demonstrates that the scale captures students’ self-efficacies in the two DfAM domains with sufficient separation. This work supports the use of the DfAM self-efficacy scale for assessing the effects of DfAM education on students’ DfAM learning in conceptual design. Moreover, the DfAM self-efficacy scale can support future research attempting to enhance the effectiveness of AM and DfAM educational interventions by measuring their effects on students’ self-perceived abilities.
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allfields	10.1007/s00163-022-00392-1 doi (DE-627)SPR048039373 (SPR)s00163-022-00392-1-e DE-627 ger DE-627 rakwb eng Prabhu, Rohan verfasserin (orcid)0000-0002-9952-2030 aut Development and validity evidence investigation of a design for additive manufacturing self-efficacy scale 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022 Abstract As additive manufacturing (AM) processes become ubiquitous in engineering and design, there has emerged the need for a workforce skilled in designing for AM (DfAM). Researchers have proposed educational interventions to train students in DfAM; however, few measures with sufficient validity evidence have been proposed to assess the effects of these educational interventions on student designers’ learning. In this paper, we present the development of a ten-item DfAM self-efficacy scale spanning the opportunistic and restrictive DfAM domains, as they relate to conceptual design (i.e., preliminary concept generation and selection). We tested the criterion-related validity of the scale by comparing students’ self-efficacy to their prior AM and DfAM experience. Additionally, we tested the construct validity of the scale through exploratory and confirmatory factor analyses. Students’ responses to the scale positively correlated with their prior experience in AM and DfAM, thereby lending criterion-related validity. Additionally, factor analyses reveal that students’ responses are composed of two dimensions: (1) opportunistic DfAM and (2) restrictive DfAM, reflecting the categorization observed in the literature. This finding lends construct validity evidence and demonstrates that the scale captures students’ self-efficacies in the two DfAM domains with sufficient separation. This work supports the use of the DfAM self-efficacy scale for assessing the effects of DfAM education on students’ DfAM learning in conceptual design. Moreover, the DfAM self-efficacy scale can support future research attempting to enhance the effectiveness of AM and DfAM educational interventions by measuring their effects on students’ self-perceived abilities. Design for additive manufacturing (dpeaa)DE-He213 Design education (dpeaa)DE-He213 Assessment (dpeaa)DE-He213 Self-efficacy (dpeaa)DE-He213 Simpson, Timothy W. aut Miller, Scarlett R. aut Meisel, Nicholas A. aut Enthalten in Research in engineering design London : Springer, 1989 33(2022), 4 vom: 12. Juli, Seite 437-453 (DE-627)271598034 (DE-600)1480792-0 1435-6066 nnns volume:33 year:2022 number:4 day:12 month:07 pages:437-453 https://dx.doi.org/10.1007/s00163-022-00392-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 33 2022 4 12 07 437-453
spelling	10.1007/s00163-022-00392-1 doi (DE-627)SPR048039373 (SPR)s00163-022-00392-1-e DE-627 ger DE-627 rakwb eng Prabhu, Rohan verfasserin (orcid)0000-0002-9952-2030 aut Development and validity evidence investigation of a design for additive manufacturing self-efficacy scale 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022 Abstract As additive manufacturing (AM) processes become ubiquitous in engineering and design, there has emerged the need for a workforce skilled in designing for AM (DfAM). Researchers have proposed educational interventions to train students in DfAM; however, few measures with sufficient validity evidence have been proposed to assess the effects of these educational interventions on student designers’ learning. In this paper, we present the development of a ten-item DfAM self-efficacy scale spanning the opportunistic and restrictive DfAM domains, as they relate to conceptual design (i.e., preliminary concept generation and selection). We tested the criterion-related validity of the scale by comparing students’ self-efficacy to their prior AM and DfAM experience. Additionally, we tested the construct validity of the scale through exploratory and confirmatory factor analyses. Students’ responses to the scale positively correlated with their prior experience in AM and DfAM, thereby lending criterion-related validity. Additionally, factor analyses reveal that students’ responses are composed of two dimensions: (1) opportunistic DfAM and (2) restrictive DfAM, reflecting the categorization observed in the literature. This finding lends construct validity evidence and demonstrates that the scale captures students’ self-efficacies in the two DfAM domains with sufficient separation. This work supports the use of the DfAM self-efficacy scale for assessing the effects of DfAM education on students’ DfAM learning in conceptual design. Moreover, the DfAM self-efficacy scale can support future research attempting to enhance the effectiveness of AM and DfAM educational interventions by measuring their effects on students’ self-perceived abilities. Design for additive manufacturing (dpeaa)DE-He213 Design education (dpeaa)DE-He213 Assessment (dpeaa)DE-He213 Self-efficacy (dpeaa)DE-He213 Simpson, Timothy W. aut Miller, Scarlett R. aut Meisel, Nicholas A. aut Enthalten in Research in engineering design London : Springer, 1989 33(2022), 4 vom: 12. Juli, Seite 437-453 (DE-627)271598034 (DE-600)1480792-0 1435-6066 nnns volume:33 year:2022 number:4 day:12 month:07 pages:437-453 https://dx.doi.org/10.1007/s00163-022-00392-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 33 2022 4 12 07 437-453
allfields_unstemmed	10.1007/s00163-022-00392-1 doi (DE-627)SPR048039373 (SPR)s00163-022-00392-1-e DE-627 ger DE-627 rakwb eng Prabhu, Rohan verfasserin (orcid)0000-0002-9952-2030 aut Development and validity evidence investigation of a design for additive manufacturing self-efficacy scale 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022 Abstract As additive manufacturing (AM) processes become ubiquitous in engineering and design, there has emerged the need for a workforce skilled in designing for AM (DfAM). Researchers have proposed educational interventions to train students in DfAM; however, few measures with sufficient validity evidence have been proposed to assess the effects of these educational interventions on student designers’ learning. In this paper, we present the development of a ten-item DfAM self-efficacy scale spanning the opportunistic and restrictive DfAM domains, as they relate to conceptual design (i.e., preliminary concept generation and selection). We tested the criterion-related validity of the scale by comparing students’ self-efficacy to their prior AM and DfAM experience. Additionally, we tested the construct validity of the scale through exploratory and confirmatory factor analyses. Students’ responses to the scale positively correlated with their prior experience in AM and DfAM, thereby lending criterion-related validity. Additionally, factor analyses reveal that students’ responses are composed of two dimensions: (1) opportunistic DfAM and (2) restrictive DfAM, reflecting the categorization observed in the literature. This finding lends construct validity evidence and demonstrates that the scale captures students’ self-efficacies in the two DfAM domains with sufficient separation. This work supports the use of the DfAM self-efficacy scale for assessing the effects of DfAM education on students’ DfAM learning in conceptual design. Moreover, the DfAM self-efficacy scale can support future research attempting to enhance the effectiveness of AM and DfAM educational interventions by measuring their effects on students’ self-perceived abilities. Design for additive manufacturing (dpeaa)DE-He213 Design education (dpeaa)DE-He213 Assessment (dpeaa)DE-He213 Self-efficacy (dpeaa)DE-He213 Simpson, Timothy W. aut Miller, Scarlett R. aut Meisel, Nicholas A. aut Enthalten in Research in engineering design London : Springer, 1989 33(2022), 4 vom: 12. Juli, Seite 437-453 (DE-627)271598034 (DE-600)1480792-0 1435-6066 nnns volume:33 year:2022 number:4 day:12 month:07 pages:437-453 https://dx.doi.org/10.1007/s00163-022-00392-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 33 2022 4 12 07 437-453
allfieldsGer	10.1007/s00163-022-00392-1 doi (DE-627)SPR048039373 (SPR)s00163-022-00392-1-e DE-627 ger DE-627 rakwb eng Prabhu, Rohan verfasserin (orcid)0000-0002-9952-2030 aut Development and validity evidence investigation of a design for additive manufacturing self-efficacy scale 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022 Abstract As additive manufacturing (AM) processes become ubiquitous in engineering and design, there has emerged the need for a workforce skilled in designing for AM (DfAM). Researchers have proposed educational interventions to train students in DfAM; however, few measures with sufficient validity evidence have been proposed to assess the effects of these educational interventions on student designers’ learning. In this paper, we present the development of a ten-item DfAM self-efficacy scale spanning the opportunistic and restrictive DfAM domains, as they relate to conceptual design (i.e., preliminary concept generation and selection). We tested the criterion-related validity of the scale by comparing students’ self-efficacy to their prior AM and DfAM experience. Additionally, we tested the construct validity of the scale through exploratory and confirmatory factor analyses. Students’ responses to the scale positively correlated with their prior experience in AM and DfAM, thereby lending criterion-related validity. Additionally, factor analyses reveal that students’ responses are composed of two dimensions: (1) opportunistic DfAM and (2) restrictive DfAM, reflecting the categorization observed in the literature. This finding lends construct validity evidence and demonstrates that the scale captures students’ self-efficacies in the two DfAM domains with sufficient separation. This work supports the use of the DfAM self-efficacy scale for assessing the effects of DfAM education on students’ DfAM learning in conceptual design. Moreover, the DfAM self-efficacy scale can support future research attempting to enhance the effectiveness of AM and DfAM educational interventions by measuring their effects on students’ self-perceived abilities. Design for additive manufacturing (dpeaa)DE-He213 Design education (dpeaa)DE-He213 Assessment (dpeaa)DE-He213 Self-efficacy (dpeaa)DE-He213 Simpson, Timothy W. aut Miller, Scarlett R. aut Meisel, Nicholas A. aut Enthalten in Research in engineering design London : Springer, 1989 33(2022), 4 vom: 12. Juli, Seite 437-453 (DE-627)271598034 (DE-600)1480792-0 1435-6066 nnns volume:33 year:2022 number:4 day:12 month:07 pages:437-453 https://dx.doi.org/10.1007/s00163-022-00392-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 33 2022 4 12 07 437-453
allfieldsSound	10.1007/s00163-022-00392-1 doi (DE-627)SPR048039373 (SPR)s00163-022-00392-1-e DE-627 ger DE-627 rakwb eng Prabhu, Rohan verfasserin (orcid)0000-0002-9952-2030 aut Development and validity evidence investigation of a design for additive manufacturing self-efficacy scale 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022 Abstract As additive manufacturing (AM) processes become ubiquitous in engineering and design, there has emerged the need for a workforce skilled in designing for AM (DfAM). Researchers have proposed educational interventions to train students in DfAM; however, few measures with sufficient validity evidence have been proposed to assess the effects of these educational interventions on student designers’ learning. In this paper, we present the development of a ten-item DfAM self-efficacy scale spanning the opportunistic and restrictive DfAM domains, as they relate to conceptual design (i.e., preliminary concept generation and selection). We tested the criterion-related validity of the scale by comparing students’ self-efficacy to their prior AM and DfAM experience. Additionally, we tested the construct validity of the scale through exploratory and confirmatory factor analyses. Students’ responses to the scale positively correlated with their prior experience in AM and DfAM, thereby lending criterion-related validity. Additionally, factor analyses reveal that students’ responses are composed of two dimensions: (1) opportunistic DfAM and (2) restrictive DfAM, reflecting the categorization observed in the literature. This finding lends construct validity evidence and demonstrates that the scale captures students’ self-efficacies in the two DfAM domains with sufficient separation. This work supports the use of the DfAM self-efficacy scale for assessing the effects of DfAM education on students’ DfAM learning in conceptual design. Moreover, the DfAM self-efficacy scale can support future research attempting to enhance the effectiveness of AM and DfAM educational interventions by measuring their effects on students’ self-perceived abilities. Design for additive manufacturing (dpeaa)DE-He213 Design education (dpeaa)DE-He213 Assessment (dpeaa)DE-He213 Self-efficacy (dpeaa)DE-He213 Simpson, Timothy W. aut Miller, Scarlett R. aut Meisel, Nicholas A. aut Enthalten in Research in engineering design London : Springer, 1989 33(2022), 4 vom: 12. Juli, Seite 437-453 (DE-627)271598034 (DE-600)1480792-0 1435-6066 nnns volume:33 year:2022 number:4 day:12 month:07 pages:437-453 https://dx.doi.org/10.1007/s00163-022-00392-1 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 33 2022 4 12 07 437-453
language	English
source	Enthalten in Research in engineering design 33(2022), 4 vom: 12. Juli, Seite 437-453 volume:33 year:2022 number:4 day:12 month:07 pages:437-453
sourceStr	Enthalten in Research in engineering design 33(2022), 4 vom: 12. Juli, Seite 437-453 volume:33 year:2022 number:4 day:12 month:07 pages:437-453
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Design for additive manufacturing Design education Assessment Self-efficacy
isfreeaccess_bool	false
container_title	Research in engineering design
authorswithroles_txt_mv	Prabhu, Rohan @@aut@@ Simpson, Timothy W. @@aut@@ Miller, Scarlett R. @@aut@@ Meisel, Nicholas A. @@aut@@
publishDateDaySort_date	2022-07-12T00:00:00Z
hierarchy_top_id	271598034
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language_de	englisch
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author	Prabhu, Rohan
spellingShingle	Prabhu, Rohan misc Design for additive manufacturing misc Design education misc Assessment misc Self-efficacy Development and validity evidence investigation of a design for additive manufacturing self-efficacy scale
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topic_title	Development and validity evidence investigation of a design for additive manufacturing self-efficacy scale Design for additive manufacturing (dpeaa)DE-He213 Design education (dpeaa)DE-He213 Assessment (dpeaa)DE-He213 Self-efficacy (dpeaa)DE-He213
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title	Development and validity evidence investigation of a design for additive manufacturing self-efficacy scale
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title_full	Development and validity evidence investigation of a design for additive manufacturing self-efficacy scale
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author_browse	Prabhu, Rohan Simpson, Timothy W. Miller, Scarlett R. Meisel, Nicholas A.
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title_sort	development and validity evidence investigation of a design for additive manufacturing self-efficacy scale
title_auth	Development and validity evidence investigation of a design for additive manufacturing self-efficacy scale
abstract	Abstract As additive manufacturing (AM) processes become ubiquitous in engineering and design, there has emerged the need for a workforce skilled in designing for AM (DfAM). Researchers have proposed educational interventions to train students in DfAM; however, few measures with sufficient validity evidence have been proposed to assess the effects of these educational interventions on student designers’ learning. In this paper, we present the development of a ten-item DfAM self-efficacy scale spanning the opportunistic and restrictive DfAM domains, as they relate to conceptual design (i.e., preliminary concept generation and selection). We tested the criterion-related validity of the scale by comparing students’ self-efficacy to their prior AM and DfAM experience. Additionally, we tested the construct validity of the scale through exploratory and confirmatory factor analyses. Students’ responses to the scale positively correlated with their prior experience in AM and DfAM, thereby lending criterion-related validity. Additionally, factor analyses reveal that students’ responses are composed of two dimensions: (1) opportunistic DfAM and (2) restrictive DfAM, reflecting the categorization observed in the literature. This finding lends construct validity evidence and demonstrates that the scale captures students’ self-efficacies in the two DfAM domains with sufficient separation. This work supports the use of the DfAM self-efficacy scale for assessing the effects of DfAM education on students’ DfAM learning in conceptual design. Moreover, the DfAM self-efficacy scale can support future research attempting to enhance the effectiveness of AM and DfAM educational interventions by measuring their effects on students’ self-perceived abilities. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022
abstractGer	Abstract As additive manufacturing (AM) processes become ubiquitous in engineering and design, there has emerged the need for a workforce skilled in designing for AM (DfAM). Researchers have proposed educational interventions to train students in DfAM; however, few measures with sufficient validity evidence have been proposed to assess the effects of these educational interventions on student designers’ learning. In this paper, we present the development of a ten-item DfAM self-efficacy scale spanning the opportunistic and restrictive DfAM domains, as they relate to conceptual design (i.e., preliminary concept generation and selection). We tested the criterion-related validity of the scale by comparing students’ self-efficacy to their prior AM and DfAM experience. Additionally, we tested the construct validity of the scale through exploratory and confirmatory factor analyses. Students’ responses to the scale positively correlated with their prior experience in AM and DfAM, thereby lending criterion-related validity. Additionally, factor analyses reveal that students’ responses are composed of two dimensions: (1) opportunistic DfAM and (2) restrictive DfAM, reflecting the categorization observed in the literature. This finding lends construct validity evidence and demonstrates that the scale captures students’ self-efficacies in the two DfAM domains with sufficient separation. This work supports the use of the DfAM self-efficacy scale for assessing the effects of DfAM education on students’ DfAM learning in conceptual design. Moreover, the DfAM self-efficacy scale can support future research attempting to enhance the effectiveness of AM and DfAM educational interventions by measuring their effects on students’ self-perceived abilities. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022
abstract_unstemmed	Abstract As additive manufacturing (AM) processes become ubiquitous in engineering and design, there has emerged the need for a workforce skilled in designing for AM (DfAM). Researchers have proposed educational interventions to train students in DfAM; however, few measures with sufficient validity evidence have been proposed to assess the effects of these educational interventions on student designers’ learning. In this paper, we present the development of a ten-item DfAM self-efficacy scale spanning the opportunistic and restrictive DfAM domains, as they relate to conceptual design (i.e., preliminary concept generation and selection). We tested the criterion-related validity of the scale by comparing students’ self-efficacy to their prior AM and DfAM experience. Additionally, we tested the construct validity of the scale through exploratory and confirmatory factor analyses. Students’ responses to the scale positively correlated with their prior experience in AM and DfAM, thereby lending criterion-related validity. Additionally, factor analyses reveal that students’ responses are composed of two dimensions: (1) opportunistic DfAM and (2) restrictive DfAM, reflecting the categorization observed in the literature. This finding lends construct validity evidence and demonstrates that the scale captures students’ self-efficacies in the two DfAM domains with sufficient separation. This work supports the use of the DfAM self-efficacy scale for assessing the effects of DfAM education on students’ DfAM learning in conceptual design. Moreover, the DfAM self-efficacy scale can support future research attempting to enhance the effectiveness of AM and DfAM educational interventions by measuring their effects on students’ self-perceived abilities. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022
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title_short	Development and validity evidence investigation of a design for additive manufacturing self-efficacy scale
url	https://dx.doi.org/10.1007/s00163-022-00392-1
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up_date	2024-07-03T16:36:21.942Z
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fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR048039373</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230509111104.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">220910s2022 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s00163-022-00392-1</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR048039373</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s00163-022-00392-1-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Prabhu, Rohan</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0002-9952-2030</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Development and validity evidence investigation of a design for additive manufacturing self-efficacy scale</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2022</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract As additive manufacturing (AM) processes become ubiquitous in engineering and design, there has emerged the need for a workforce skilled in designing for AM (DfAM). Researchers have proposed educational interventions to train students in DfAM; however, few measures with sufficient validity evidence have been proposed to assess the effects of these educational interventions on student designers’ learning. In this paper, we present the development of a ten-item DfAM self-efficacy scale spanning the opportunistic and restrictive DfAM domains, as they relate to conceptual design (i.e., preliminary concept generation and selection). We tested the criterion-related validity of the scale by comparing students’ self-efficacy to their prior AM and DfAM experience. Additionally, we tested the construct validity of the scale through exploratory and confirmatory factor analyses. Students’ responses to the scale positively correlated with their prior experience in AM and DfAM, thereby lending criterion-related validity. Additionally, factor analyses reveal that students’ responses are composed of two dimensions: (1) opportunistic DfAM and (2) restrictive DfAM, reflecting the categorization observed in the literature. This finding lends construct validity evidence and demonstrates that the scale captures students’ self-efficacies in the two DfAM domains with sufficient separation. This work supports the use of the DfAM self-efficacy scale for assessing the effects of DfAM education on students’ DfAM learning in conceptual design. Moreover, the DfAM self-efficacy scale can support future research attempting to enhance the effectiveness of AM and DfAM educational interventions by measuring their effects on students’ self-perceived abilities.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Design for additive manufacturing</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Design education</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Assessment</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Self-efficacy</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Simpson, Timothy W.</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Miller, Scarlett R.</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Meisel, Nicholas A.</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Research in engineering design</subfield><subfield code="d">London : Springer, 1989</subfield><subfield code="g">33(2022), 4 vom: 12. Juli, Seite 437-453</subfield><subfield code="w">(DE-627)271598034</subfield><subfield code="w">(DE-600)1480792-0</subfield><subfield code="x">1435-6066</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:33</subfield><subfield code="g">year:2022</subfield><subfield code="g">number:4</subfield><subfield code="g">day:12</subfield><subfield code="g">month:07</subfield><subfield code="g">pages:437-453</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s00163-022-00392-1</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="912" 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