Acceptance of socially assistive humanoid robot by preschool and elementary school teachers Marina Fridin a,⇑ , Mark Belokopytov b a Faculty of Industrial Engineering and Management, Ariel University Center, POB 3, Kiryat Hamada, Ariel 40700, Israel b Human Motion Analysis Laboratory, Assaf Harofeh Medical Center, Zerefin 60930, Israel article info Article history: Available online 15 January 2014 Keywords: Social assistive robotics Unified Theory of Acceptance and the Use of Technology Teacheracceptance abstract This study examined the first-time acceptance of (SAR) by preschool and primary school teachers. A mod- ified Unified Theory of Acceptance and the Use of Technology model was applied using the questionnaires filled out by 18 teachers following interactions with a robot. The participants demonstrated positive reac- tions and acceptance accompanied by a variety of answers. The lack of consolidated views in the tested population of teachers and the need for an adaptation of the model are suggested. The future intensive research of teacher–acceptance of SAR will avoid the gap between technology and the end-user. Ó 2013 Elsevier Ltd. All rights reserved. 1. Introduction 1.1. Acceptance of technologies by teachers The acceptance of innovative educational technology by teach- ers is a crucial issue, especially since technology-supported educa- tional practices are becoming increasingly introduced and implemented in the teaching process (Alavi, 1994; Hiltz, 1994; Jonassen, Peck, & Wilson, 1999; McKendree, Stenning, Mayes, Lee, & Cox, 1998). Without the teacher’s acceptance, educational technology cannot hope to deliver whatever value it may hold (Zhao, Hueyshan, & Mishra, 2001). Technology acceptance can be defined as, ‘‘a user’s willingness to employ technology for the tasks it is designed to support’’ (Dillon & Morris, 1996). Despite research that shows the capability of technology to facilitate teaching and learning, the use of technology in the class- rooms remains insufficient and teachers do not use technology effectively enough (Bourgonjon et al., 2013; Hu, Clark, & Ma, 2003; Lim & Khine, 2006). Researchers have identified several fac- tors that influence the adoption and integration of technology into teaching. These factors include: user characteristics, content char- acteristics, technological considerations, and organizational capac- ity (Balanskat, Blamire, & Kafal, 2006; Buabeng-Andoh, 2012; Clausen, 2007; Lim & Chai, 2008; Rogers, 2003; Stockdill & Morehouse, 1992; Tondeur, Valcke, & van Braak, 2008). On the other hand, the use of technologies in educational process is inten- sively studied and their high acceptance among the students have been proved (Cheng, Lou, Kuo, & Shih, 2013; Furió, González- Gancedo, Juan, Seguí, & Rando, 2013). At the current level of technology development, the majority of research is focused on user characteristics. Of the research done on humans’ interaction with and acceptance of robots in the class- room, only few studies have concentrated on the teacher’s side; the majority of the studies have investigated student–robot inter- actions (see Buabeng-Andoh, 2012 for review). 1.2. Socially Assistive Robotics in education SAR is the class of robotics that provides assistance to human users through social, rather than physical, interaction (Feil-Seifer & Mataric ´, 2011). SAR has been used in critical areas in medical care to automate supervision, coaching, motivation, and compan- ionship aspects of interactions with vulnerable individuals. Cur- rently, the main populations in which SAR has been tested and applied are the elderly (Heerink, Krose, Evers, & Wielinga, 2008; Heerink, Krose, Wielinga, & Evers, 2009a; Saini, De Ruyter, Marko- poulos, & Van, 2005; Zaad & Allouch, 2008), patients with demen- tia (Tapus, Tapus, & Mataric ´, 2009) and cognitive/motor disorders (Wainer, Feil-Seifer, Shell, & Mataric ´ , 2006), and children with aut- ism (Goodrich, Colton, Brinton, & Fujiki, 2011; Thota, Kearney, Boirum, Bojedla, & Lee, 2011; Villano et al., 2011). In the field of child care, several studies have shown the positive impact of SAR on typically developing children and children with social disorders (Kozima, Nakagawa, & Yano, 2004; Tanaka, Move- llan, Fortenberry, & Aisaka, 2006). iRobi, a humanoid teaching- assistant robot, has been tested in elementary schools (Han, Jo, Park, & Kim, 2005; Han & Kim, 2009; Kanda, Hirano, Eaton, & Ishiguro, 2004; Shin & Kim, 2007; You, Shen, Chang, Liu, & Chen, 0747-5632/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.chb.2013.12.016 ⇑ Corresponding author. Tel.: +972 3 9371411; fax: +972 3 9066322. E-mail address: marinafridin@gmail.com (M. Fridin). Computers in Human Behavior 33 (2014) 23–31 Contents lists available at ScienceDirect Computers in Human Behavior journal homepage: www.elsevier.com/locate/comphumbeh