*Undergraduate Directed Research*

Felicia Grasso (with Jody Garcia):
Jody's work centers on language contact and historical language change. My work with
Jody’s research included translating a number of texts in different dialects of German
to English. I took a look at translation theory, the issues that have arisen over the years
in translation. I gave a sample of specific issues I ran into when translating dialects and
outdated German texts into English, and show how I chose to face these issues. I show
my work was heavily influenced by Nida's concept of equivalence through the translation
of poetry. Nida argues that “one of the most essential, and yet often neglected, elements
is the expressive factor, for people must also feel as well as understand what is said.” In
my translation of works from Heine and others, I have experienced the same struggle in
expressing emotion of the original author, felt when read in the source text.

Mara Katz:
My research involves historical analysis of Somali Bantu Kizigua, an underdocumented language from the Bantu family spoken by members of the Somali refugee community in Pittsburgh. I am documenting the morphosyntactic structures of the language, with the goal of creating a teachable grammar, as well as performing comparative historical analysis to determine how much the language differs from related languages as well
as earlier forms of itself.

Anisa Mughal (with Nausica Marcos):
Syntactic awareness (SA) is the knowledge of a word category without necessarily knowing what the word itself means (Kieffer & Lesaux, 2012). SA is an attribute of derivational morphology that reflects a second language learner’s knowledge of how affixes of words change the meaning of a word (Kieffer & Lesaux). Testing for SA was conducted with 225 English-speaking L2 learners of Spanish at different proficiency levels. These learners completed an SA task that tested knowledge of Spanish nouns, adjectives and verbs. Preliminary results support the hypothesis that SA increases with proficiency.

"Not All Clauses are Created Equal: Classifying Complexity in ESL Speech"
Jessica Packer (with Mary Lou Vercellotti):
“Complex language” has been defined as language which utilizes a diverse range of
structures. This conceptualization presents complexity as one means of gauging language
proficiency over time. In the past, SLA researchers have combined finite and non-finite clauses when reporting on structural complexity. Within such coding systems, finite clauses and non- finite clauses with a complement or adjunct were considered equal as “clauses,” where complexity could then be gauged in global terms (words per sentence), by subordination (clauses per sentence), and subphrasally (words per clause). This classification schema has presented with weaknesses in its ability to gauge proficiency level in language learns. Thus, it has been proposed that it is likely obscuring the multi-faceted nature of structural complexity. On this basis, this research proposes a new classification scheme which recognizes the following: independent clauses, conjunctive verb phrase clauses, subordinate clauses, complementizer clauses, and relative clauses. These new classifications are derived from theoretical literature on clause acquisition and also from English language instruction curriculum material. The classification scheme is applied to production data taken from L2 instructed English learners over real time and the frequencies of learners’ production of these clauses over time are considered in order to characterize the development of complexity.

"An Analysis of Minimum Pause Durations"
Spencer Onuffer (with Mary Lou Vercellotti):
This study hopes to determine the most efficient and accurate measures of fluency and pause. It uses thirteen minimum pause lengths one data set to create a comparison of the same results using different measures. This data may be able to determine if there is a specific pause length at which a pause is no longer the same type of pause: for example if there is a notable difference between a short and long pause it will determine at what length a pause becomes long. The data will also be used to determine what measures are most affected by the different minimum pause lengths. The data will also be used to display the results in terms of trade-off effects using mean length of fluent run and mean length of utterance to display if the data can display a relation between complexity accuracy and fluency. "