YARSI UNIVERSITY PROGRAM TO MEET THE DEMAND OF STUDENT’S ENGLISH FLUENCY WITH TOEIC AS THE ASSESSMENT TOOL

Abstract: A test is only a measurement tool of a learning process. The important part is the learning process itself; how the process can help learners acquire English as a foreign language that enables them to compete in the working environment. To measure the process, TOEIC with all its parts was meant to measure learners’ ability to communicate in English. Teachers should not be focusing on the test but more on the approaches that allow the students to have adequate and sophisticated listening, reading, and writing skills to exchange information and to negotiate meaning in real life. Many university level English teachers are trapped within the rules that students should achieve a 550 or 605 TOEIC score to graduate. Instead of helping the students to acquire the language as a communication tool, they tend to focus more on getting the students to master the test. This is what teachers should deal with, not only facilitate students to learn the language but at the same time help them to do the test well. Despite the challenge of facing students who lack motivation and have very basic English skills, Yarsi University Language Lab is setting up several programs and approaches that allow students to acquire the language and enable them to communicate in the target language which is eventually measured by an instrument called TOEIC. Keywords: Language Acquisition, direct and indirect test, discrete and intregativ

cis-reQTL mapping and <i>SLC45A2</i> reQTL.

<p>(A) Outline of the approach for mapping cis-reQTLs (B) QQ plot of the cis-reQTL p-value for all genes tested. Red indicates the top 3 genes discussed in the text and used in subsequent analyses. (C) Normalized fold change of <i>SLC45A2</i> expression separated by genotype at the cis-reQTL (rs12653176). p-value calculated from the Spearman correlation. (D) Normalized <i>SLC45A2</i> expression of the NSE and SE samples separated by genotype at the same locus. p-values calculated from the Spearman correlation. (E) Manhattan plot of the fold change (FC), NSE sample expression, and SE sample expression associations with all SNPs one megabase surrounding <i>SLC45A2</i>. p-values calculated from the Spearman correlation.</p

Sun-exposed and non-sun-exposed skin samples.

<p>(A) First and second principal components of all GTEx samples with selected tissue-types highlighted by color. (B) First and second principal components using all genes in only the skin samples. (C) Fold enrichment of 2-fold differentially expressed genes from Choi <i>et al</i>. [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006382#pgen.1006382.ref043" target="_blank">43</a>] as a function of the stringency in calling differentially expressed genes from the GTEx samples.</p

Differential cis-eQTL mapping and validation with ASE.

<p>(A) Outline of our approach to mapping differential cis-regulation. (B) The expression of <i>SIM2</i> for each exposure-type after segregation by genotype at the eQTL (rs2248813). P-values are from the asymptotic approximation of the Spearman correlation (rho). (C) ASE validation of the <i>SIM2</i> result for individuals heterozygous at the eQTL. The allele on the y-axis indicates the allele at the eQTL (see x-axis of panel B), and the ASE directionalities were phased based on these alleles. * indicates p-value < 0.05 by t-test. (D) QQ plot of each tested gene after combining the effect size test and the differential ASE test. Red indicates the gene had a significant GxE expression interaction with a SNP (FDR < 0.05, Benjamini-Hochberg).</p

Testing se-eQTLs for signs of local adaptation.

<p>Environmental correlations with allele frequency in (A) HGDP populations and (B) Lazaridis et al [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006382#pgen.1006382.ref062" target="_blank">62</a>] populations. Left panels: Heatmap of the environmental variables used in the study. Units are Watts per meter squared. Populations are marked with blue circles. Note that three of the American populations from Lazaridis <i>et al</i>. (Mixe, Mixtec, and Zapotec) [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006382#pgen.1006382.ref062" target="_blank">62</a>] are marked in the same geographic location. Right panels: Radiation level vs allele frequency of the population for the <i>RASSF9</i> se-eQTL (rs11117173) with the color indicating the regional subgroup. For each regional subgroup, the Spearman correlation (Rho), the number of individuals (Ind), and the number of populations (Pop) are provided in the table.</p

RNA-seq reveals candidate genes.

<p><b>A.</b> Citrinin has largely similar effects on <i>Sc</i> alleles and <i>Sp</i> alleles in the <i>Sc</i>/<i>Sp</i> hybrid; i.e. ASE is similar with or without citrinin. <b>B.</b> Candidate genes were identified based on having strong <i>Sp</i>-biased ASE (in YPD; FDR < 0.05) [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005751#pgen.1005751.ref016" target="_blank">16</a>], and strong up-regulation in response to citrinin (of both <i>Sc</i> and <i>Sp</i> alleles; the smaller of these two in our RNA-seq data is plotted; binomial <i>p</i> < 10⁻⁵ for each biological replicate of each allele).</p

Promoter replacement reveals contributions of individual regulatory regions.

<p><b>A.</b> Illustration of our promoter replacement strategy. Green promoters on the left are from <i>Sc</i>, blue promoters on the right are from <i>Sp</i>. <b>B.</b> RNA-seq in the <i>Sc</i>/<i>Sp</i> hybrid, which measures the overall <i>cis-</i>regulatory divergence between these strains, is in approximate agreement with the effect of the promoter replacements, measured by qPCR (<i>r</i> = 0.92). Error bars show 1 S.E. <b>C.</b> After competitive growth for 40 generations, promoter replacement strains for 3/4 candidate genes show a similar pattern of fitness advantage in the presence of 300 ppm citrinin, and disadvantage in its absence. Error bars show 1 S.E.</p

Results of the sign test for selection on <i>cis-</i>regulation.

<p>For a description of the test and its results, see the main text and Methods. Note that only two citrinin-induced genes are shown, but four were present in the top 1% of <i>Sp</i>-biased genes, and ten in the top 25%.</p

Effects of candidate gene deletion and over-expression.

<p><b>A.</b> The five candidate genes were deleted from <i>Sp</i>, and the effect on resistance to 300 ppm citrinin was measured. Four deletions increased sensitivity (t-test <i>p</i> < 0.005 for each), and were studied further. Error bars show 1 S.E. <b>B.</b> The effects of three different dCas9 fusion proteins targeted to four candidate genes were measured by qPCR. <b>C.</b> Illustration of our strategy to over-express four genes via dCas9 fusion protein. <b>D.</b> We used direct competition for 40 generations to measure the relative fitness of the four-gene over-expression strain (with a Gal4-dCas9-VP64 dual fusion) vs. a control strain containing the same plasmid, but lacking any gRNAs. Conditions were YPD, and YPD + 300 ppm citrinin. Error bars show 1 S.E.</p

A polygenic gene expression adaptation in the ergosterol biosynthesis (ERG) pathway.

<p>(<b>A</b>) The final steps of the ERG pathway. Eight genes whose down-regulation contributes to a polygenic gene expression adaptation are colored red; the six previously implicated genes <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003813#pgen.1003813-Fraser4" target="_blank">[8]</a> are underlined. Erg28 is shown next to its strongest interaction partner, Erg27. (<b>B</b>) Allelic bias of ERG genes, as measured by pyrosequencing in the RM/BY hybrid. The allelic bias indicates the magnitude of <i>cis-</i>regulatory divergence between RM and BY for each gene. Red color indicates genes that are part of the polygenic adaptation. Asterisks indicate those that interact strongly with Erg28 <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003813#pgen.1003813-Mo1" target="_blank">[24]</a>, all of which have stronger allelic bias than those that do not.</p