Learning Computerese

Abstract

This article introduces a new construct coined as Computer User Learning Aptitude (CULA). To establish construct validity, CULA is embedded in a nomological network that extends the technology acceptance model (TAM). Specifically, CULA is posited to affect perceived usefulness and perceived ease of use, the two underlying TAM constructs. Furthermore, we examine several antecedents of CULA by relying on the second language learning literature. These include computer anxiety, tolerance of ambiguity, and risk taking. Conceptualization of CULA is based on the observation that computer systems use language as communication between the computer and the user, making system usage significantly dependent on the ability of the individual to learn the language. We posit that learning to communicate with computer technology is akin to learning a second language, that is, a language learned after the first language(s) or native language(s), and is referred to as computerese. The proposed construct, CULA, measures the aptitude of an individual to learn computerese, and it is specified as a second-order variable. It includes measures of three critical facets of computerese pertaining to general hardware/software, programming, and the Internet. Significant relationships are found between computer anxiety, tolerance of ambiguity, and taking risk with CULA, as well as between CULA and TAM constructs.

Flipped Classroom Research and Trends from Different Fields of Study

“…The quantitative research of the flipped classroom has been conducted by numerous researchers (e.g., Baepler, Walker, & Driessen, 2014;Chen & Summers, 2015;Love, Hodge, Grandgenett, & Swift, 2014;McLaughlin et al, 2014;Missildine, Fountain, Summers, & Gosselin, 2013;Tune, Sturek, & Basile, 2013;Touchton, 2015;Warner, Koufteros, & Verghese, 2014. In collecting the data, Beapler et al…”

“…The third were college students without detailed information whether undergraduate or graduate level (e.g. Warner et al, 2014;Love et al, 2014;Missildine et al, 2013). Then, only a study by Kong (2014) used students as participants without having specified from which level of education they were enrolled.…”

“…Various studies in flipped classroom in 2013, 2014 and 2015 showed different fields of studies, including science and social courses, such as information systems (Davies et al, 2013), chemistry (Baepler et al, 2014), algebra (Love et al, 2014), economics (Roach, 2014), engineering, sociology and humanities (Kim et al, 2014), integrated humanities (Kong, 2014), physiology (Talley & Scherer, 2013), statistics (Touchton, 2015), public health (Simpson & Richards, 2015 (Warner et al, 2014), and English language (Hung, 2015).…”

Bibliometric Analysis of Ambiguity Tolerance: Unearthing Its Role in Sustainable Language Education

“…The perceived ease of use (PEOU) of immersive technology is that it could simulate relaxing and comfortable learning atmospheres [68,69]. AT is empirically confirmed as a significant variable in technology acceptance models (TAMs) for the adoption of AI technologies [72,73]. Future research could combine empirical methods to investigate the function of AT in utilizing advanced technologies by extending the Technology Acceptance Model (TAM) by adding the personality attribute AT.…”