Machine translation (MT) studies for English-Turkish language pair date back to early 1960's. These studies seem to be interrupted for a long period of time but got momentum in early 2000's. The main barriers in front of MT studies for English-Turkish are morphological and syntactic differences between these two languages. Although not proven empirically yet, in Turkey, translation is perceived by many people as a profession which can also be performed by non-professionals, which can affect the supplydemand balance in the market. This situation may constitute another barrier in that sense.The introduction and the use of machine translation and computer-aided translation tools in the translation curriculum and identification of their advantages and shortcomings has a potential to contribute to the professional development of prospective translators as well as to provide a foundation for studies to be conducted in the field of MT. The current study investigates the opinions of novice translators about machine translation in general, its contribution to the translation process, and about computer-aided translation tools. Data were collected from 106 third-year translation students within the framework of a compulsory course on translation technologies. Data include students' comments about translation tasks that they completed using Google Translate system on Google Translator Toolkit - an online translation memory system - and their answers to the survey questions which were administered at the end of the semester. The participants, as part of their term project for the 15-week long course on translation technologies, translated the source texts using Google Translate within Google Translator Toolkit and post-edited the machine translation output in this translation memory system with the help of a terminology management tool. Finally, they inserted comments for translations conducted by their peers and gave feedback about the quality of machine translation.It is clear that the general quality of English-Turkish machine translation provided by Google has not improved much between 2010 and 2013 according to the participants' comments, notwithstanding technical developments such as speech-to-text, text-to-speech, improving machine translation by inserting suggestions, and ever-increasing size of parallel text database that Google Translate is utilizing. The analysis of data suggests that Google MT output is usually considered unacceptable. However, most students acknowledge the potential of MT for producing a draft translation. Prospective translators are quite enthusiastic about the benefits of computer-aided tools such as translation memory system and terminology management systems as provided within Google Translator Toolkit. This suggests that translation students' general negative attitude towards machine translation results from the low quality of the output that Google Translate produces, and that students do not show the same attitude towards using computers as an aid in the translation process.