People in educational settings are expected to effectively use increasingly complex technology. One of the most important factors in technology use is computer self-efficacy (CSE). Although frequently assessed, available measures of CSE have various issues. Additionally, there is no current measure that delineates CSE at different skill levels and specifically targets usage in applied fields. Consequently, this set of seven studies describes the development and psychometric properties of two CSE scales that address these issues: the 18-item Brief Inventory of Technology Self-Efficacy (BITS) and the six-item Brief Inventory of Technology Self-Efficacy – Short Form (BITS-SF). The first study encompassed conceptualization and item development. The second and third studies explored and confirmed the three-factor structure of the BITS (Novice, Advanced, and Expert) in samples of Mechanical Turk workers and college students, respectively. The fourth study examined the multigroup invariance of this factor structure across men and women. The fifth study showed evidence for the temporal stability of the BITS. The sixth study assessed for validity evidence for both scales. Finally, the seventh study used latent class analysis to determine the underlying classes of the BITS-SF. The uses of the BITS and BITS-SF are discussed. Both measures are available at www.bitssurvey.com.

人们期望处于教育环境中的人们能够有效地使用日益复杂的技术。技术使用中最重要的因素之一是计算机自我效能（CSE）。尽管经常进行评估，但可用的CSE度量标准存在许多问题。此外，目前没有方法可以描述不同技能水平的CSE，并专门针对应用领域中的使用情况。因此，这套七项研究描述了解决这些问题的两个CSE量表的发展和心理计量特性：18个项目的技术自我效能简要清单（BITS）和6个项目的技术自我效能简要清单-简短表格（BITS-SF）。第一项研究包括概念化和项目开发。第二和第三项研究探索并确认了BITS的三要素结构（新手，高级，和专家）分别来自“机械特克”工人和大学生的样本。第四项研究考察了男性和女性中这一因素结构的多组不变性。第五项研究显示了BITS的时间稳定性的证据。第六项研究评估了两个量表的有效性证据。最后，第七项研究使用潜在类别分析来确定BITS-SF的基础类别。讨论了BITS和BITS-SF的用途。两种措施都可以在www.bitssurvey.com上获得。第七项研究使用潜在类别分析来确定BITS-SF的基础类别。讨论了BITS和BITS-SF的用途。两种措施都可以在www.bitssurvey.com上获得。第七项研究使用潜在类别分析来确定BITS-SF的基础类别。讨论了BITS和BITS-SF的用途。两种措施都可以在www.bitssurvey.com上获得。